the impact of entrepreneurship education on the ... · university education is no longer a passport...
TRANSCRIPT
The Impact of Entrepreneurship Education on the
Relationships between Institutional and Individual
Factors and Entrepreneurial Intention of
University Graduates: Evidence from Zambia
Bruce M.K. Mwiya BBA, MBA, MIP
Commonwealth Scholar, funded by the UK government
A thesis submitted in partial fulfilment of the requirements of
the University of Wolverhampton for the Degree of
Doctor of Philosophy
October 2014
This work or any part thereof has not previously been presented in any form to the
University or to any other body whether for the purposes of assessment,
publication or for any other purpose (unless otherwise indicated). Save for any
express acknowledgments, references and/or bibliographies cited in the work, I
confirm that the intellectual content of the work is the result of my own efforts and
of no other person.
The right of Bruce M.K. Mwiya to be identified as author of this work is asserted in
accordance with ss.77 and 78 of the Copyright, Designs and Patents Act 1988. At
this date copyright is owned by the author.
Signature ……………Bruce M.K. Mwiya Date …………………30th January 2015
i
Abstract
University education is no longer a passport to secure employment for graduates.
This requires young graduates to consider entrepreneurship and self-employment
as a viable career option. Understanding the determinants of entrepreneurial
intention (EI), therefore, becomes important. In exploring the determinants of EI,
prior studies investigate the effects of individual factors, contextual factors and
entrepreneurship education (EE) in isolation from each other. Moreover, literature
on the effect of EE on EI shows mixed conclusions. The current study, by
considering EE as the kernel, firstly examines individual and institutional
determinants of EI. Secondly, it explores whether EE affects the relationships
between EI and its individual and institutional determinants. To avoid bias from
utilising one particular methodology, this study purposely employed a concurrent
triangulation strategy. This was intended for model testing and in-depth
understanding of the research issues in the Zambian context. Primary data were
collected from Zambia via qualitative interviews and a quantitative survey. For the
qualitative study, 13 interviews were conducted and interviewees included final
year undergraduate students, educators and practitioners in enterprise support
organisations. For the quantitative study, 452 useful responses were received from
final year undergraduate students. Research results suggest that, firstly, EI is
primarily a function of perceived feasibility and desirability of entrepreneurship.
Secondly, individual and institutional factors directly influence perceived feasibility
and desirability of entrepreneurship. Thirdly, and more importantly, individual and
institutional factors indirectly exert their impact on perceived feasibility and
desirability via EE.
The study contributes to knowledge in four major areas. Firstly, against the
backdrop of mixed conclusions in prior research about the effect of EE on EI, this
ii
study finds that the effect of EE should be examined in conjunction with factors at
individual and institutional levels. Specifically, it establishes that effectiveness of
EE mediates the effects of individual and institutional factors on perceived
feasibility and desirability of entrepreneurship i.e. the attitudinal antecedents of EI.
This helps clarify the role of EE. Secondly, unlike prior studies and models that
examine the influence of EE, individual factors and contextual factors in isolation
from each other, this study develops and validates a multi-level integrated model
to explore how these factors jointly shape EI. Specifically, the model shows that
factors at individual and institutional levels influence EI not only through their
effects on perceived feasibility and desirability but also through their impact on the
effectiveness of EE. Thirdly, the study provides evidence from Zambia, an under-
researched developing country, that EI is primarily a function of perceived
feasibility and desirability of entrepreneurship. This supports prior research
conclusions from developed countries. Lastly, the study further develops and
validates constructs for EE, providing a basis for evaluating EE. In particular, it
demonstrates that effectiveness of EE in relation to EI can be evaluated from three
angles: perceived learning from the module/programme, experiential learning and
access to resources. On the whole, the findings derived suggest that, in order to
promote graduate entrepreneurship, multifaceted and concerted efforts will be
required from policy makers (to help shape institutions), practitioners (to devise
and implement collaborative support mechanisms), educators (to design and
deliver appropriate EE content and pedagogy) and scholars (to evaluate and
develop knowledge).
iii
Acknowledgements
I am entirely responsible for the work presented in this thesis. However, at the
same time I acknowledge that work of this magnitude and depth can never be
solely the effort of one individual. There are many stakeholders to thank. I am
greatly indebted to the Commonwealth Scholarships Commission (UK) for offering
the Commonwealth Academic Staff Scholarship, the Coppebelt University for
granting the study leave, and the University of Wolverhampton Business School’s
Management Research Centre for facilitating the research project. I am also
indebted to my supervisors, Dr Yong Wang (Director of Studies), Dr Ian Mckeown
and Dr Graham Tate for guiding me through this study. Without Dr Yong Wang’s
dedicated direction, mentoring and support, this project would not have been
finished properly.
Special thanks go to the eight universities in Zambia which authorised and
facilitated access to the final year students for the survey. Special gratitude also
goes to the lecturers, students and enterprise support practitioners in Zambia who
participated in the interviews. I am also grateful to all the staff at the University of
Wolverhampton for their support. Particularly, I wish to thank Prof Silke Machold,
Prof Mike Haynes, Prof Les Worrall, Dr Paschal Anosike, Dr Stuart Farquhar and
Steven Greenfield for their encouragement and support. I thank Andy (Dr Jones),
David and Aurelian (Dr Mbzibain) for all the insightful discussions in ML119 and
ML120.
Lastly, words are not adequate for appreciating my wife and best friend Bernadette
and our children Bruce, Grace and Benita for their encouragement and sacrifice
during this research project. I end this section with gratitude to God for life and
blessing.
iv
TABLE OF CONTENTS
Abstract .................................................................................................................................. i
Acknowledgements ............................................................................................................... iii
List of Appendices .............................................................................................................. viii
List of Figures ....................................................................................................................... ix
List of Tables ......................................................................................................................... x
List of Abbreviations and Acronyms ..................................................................................... xii
List of Key Definitions ........................................................................................................ xiv
CHAPTER 1: INTRODUCTION TO THE RESEARCH ......................................................... 1
1.1 Outline of the Research Project ...................................................................................... 1
1.1.1 Rationale of the Study and Research Problems ....................................................... 3
1.1.2 Aims and Objectives of the Study ............................................................................. 6
1.2 Contributions to Knowledge ............................................................................................ 6
1.3 Summary of the Thesis Contents .................................................................................... 8
CHAPTER 2: RESEARCH BACKGROUND - ZAMBIAN CONTEXT ................................. 11
2.0 Introduction ................................................................................................................... 11
2.1 Zambian History and Culture ....................................................................................... 11
2.2 Structure of Zambia’s Economy and Its Challenges ...................................................... 17
2.2.1 Diversification Efforts and Entrepreneurship ......................................................... 21
2.2.2 Challenges of Unemployment for the Youth ........................................................... 24
2.3 Institutional Support for Start-ups and SMEs................................................................. 26
2.3.1 Entrepreneurial Activity in Zambia based on GEM Surveys .................................... 31
2.4 Graduate Unemployment and Graduate Entrepreneurship ........................................... 32
2.4.1 Graduate Unemployment ....................................................................................... 32
2.4.2 Graduate Entrepreneurship .................................................................................... 33
2.4.3 Entrepreneurship Education in Higher Education in Zambia ................................... 35
2.5 Conclusions .................................................................................................................. 36
CHAPTER 3: ENTREPRENEURSHIP – HISTORICAL AND THEORETICAL OVERVIEW 38
3.0 Introduction ................................................................................................................... 38
3.1 The Classical Approach ................................................................................................ 38
3.1.1 Classical Views of the Entrepreneur ....................................................................... 38
3.1.2 Neo-Classical Views ............................................................................................... 43
3.1.2.1 Kirznerian Entrepreneurship ............................................................................ 44
3.1.2.2 Schumpeterian Entrepreneurship ..................................................................... 46
3.2 Psychological Approach ................................................................................................ 49
3.2.1 Personality and Motives ......................................................................................... 51
3.2.2 Core Self–Evaluation Characteristics ..................................................................... 53
3.2.3 Cognitive Characteristics ........................................................................................ 55
v
3.2.4 Overall Critique of Psychological Trait Approach .................................................... 56
3.3 Sociological Approach .................................................................................................. 57
3.3.1 Family Background ................................................................................................. 59
3.3.2 Social, Situational and other Background Factors .................................................. 59
3.3.3 Supportive Entrepreneurial Environment (Institutional Factors) .............................. 60
3.4 Processual View of Entrepreneurship .......................................................................... 62
3.6 Conclusions .................................................................................................................. 65
CHAPTER 4: INTENTIONALITY OF ENTREPRENEURSHIP ........................................... 66
4.0 Introduction ................................................................................................................... 66
4.1 The Role of Intention in the Process of Venture Creation .............................................. 66
4.2 Review of Prominent Entrepreneurial Intention Models ................................................. 68
4.2.1 Bird (1988): The Contexts of Intentionality .............................................................. 69
4.2.2 Azjen (1991): The Theory of Planned Behaviour .................................................... 72
4.2.3 Shapero and Sokol (1982): Entrepreneurial Event Model ....................................... 74
4.2.4 Comparison of TPB and SEE Models ..................................................................... 76
4.3 Further Development of the EI Model Required ............................................................ 77
4.4 Conclusions .................................................................................................................. 79
CHAPTER 5: ENTREPRENEURSHIP EDUCATION – IMPORTANCE, TYPES AND
EFFECTS ........................................................................................................................... 81
5.0 Introduction ................................................................................................................... 81
5.1 Importance of Entrepreneurship Education ................................................................... 81
5.2 Types of Enterprise and Entrepreneurship Education ................................................... 84
5.2.1 Enterprise and Enterprise Education ...................................................................... 85
5.2.2 Entrepreneurship and Entrepreneurship Education ................................................ 87
5.2.2.1 Debate on whether or not Entrepreneurship can be Taught ............................. 88
5.3 Effects of Entrepreneurship Education on Entrepreneurial Intention ............................. 95
5.5 Conclusions ................................................................................................................ 101
CHAPTER 6: CONCEPTUAL MODEL AND HYPOTHESES DEVELOPMENT ............... 102
6.0 Introduction ................................................................................................................. 102
6.1 Theoretical Background to the Conceptual Model ....................................................... 102
6.2 Institutional Factors’ Influence on Perceived Feasibility and Desirability ..................... 106
6.3 Individual Factors’ Influence on Perceived Feasibility and Desirability ........................ 112
6.4 Intervening Role of Entrepreneurship Education ......................................................... 119
6.4.1 Entrepreneurship Education Mediating the Influence of Institutions ...................... 121
6.4.2 Entrepreneurship Education Mediating the Influence of Individual Factors ........... 124
6.5 Influence of Perceived Feasibility and Desirability on EI ............................................. 127
6.6 Conclusions ................................................................................................................ 129
vi
CHAPTER 7: RESEARCH DESIGN, METHODS AND TECHNIQUES ............................ 130
7.0 Introduction ................................................................................................................. 130
7.1 Research Design Choice, Justifications and Implementation ...................................... 130
7.1.1 Research Philosophy ........................................................................................... 131
7.1.2 Research Approaches and Theory ....................................................................... 137
7.1.3 Research Strategies ............................................................................................. 140
7.1.4 Justification for Research Strategy and Methods .................................................. 144
7.2 Population and Samples ............................................................................................. 147
7.2.1 Qualitative Study: Sample, Data Collection and Demographic Profile ................... 150
7.2.2 Quantitative Study: Sample, Data Collection and Demographic Profile ................ 153
7.3 Measurements and Scales – Quantitative Study ......................................................... 158
7.4 Construct Validity Analyses Results - Quantitative Study ............................................ 163
7.5 Measurement Reliability Analyses Results - Quantitative Study .................................. 168
7.6 Statistical Controls and Common Methods Bias – Quantitative Study ......................... 172
7.7 Conclusions ................................................................................................................ 173
CHAPTER 8: QUALITATIVE RESEARCH FINDINGS ..................................................... 175
8.0 Introduction ................................................................................................................. 175
8.1 Findings on Individual and Institutional Factors Influencing EI .................................... 175
8.1.1 Institutional Factors’ Influence on EI ..................................................................... 175
8.1.2 Individual and Background Factors’ Influence on EI ............................................. 190
8.2. The Intervening Role of EE on Effects of Factors Influencing EI ................................ 195
8.2.1 EE Intervening in the Effects of Institutional Factors on EI .................................... 195
8.2.2 EE Intervening in the Effects of Individual Factors on EI ....................................... 201
8.3 Implications of Findings to the Conceptual Model ....................................................... 206
8.4 Conclusions ................................................................................................................ 208
CHAPTER 9: QUANTITATIVE RESEARCH FINDINGS .................................................. 210
9.0 Introduction ................................................................................................................. 210
9.1 Correlation Analyses among all Variables ................................................................... 210
9.2 Regression Tests for the Entrepreneurial Intention Model ........................................... 214
9.2.1 Effects of Perceived Feasibility and Desirability on EI… ....................................... 216
9.2.2 Determinants of Feasibility and Desirability .......................................................... 216
9.3. Statistical Mediation Analyses ................................................................................... 223
9.3.1 Statistical Mediation Analyses Procedures ........................................................... 225
9.4 The Mediating Role of Entrepreneurship Education .................................................... 227
9.4.1 EE Mediating the Effects of Institutions on Feasibility and Desirability .................. 227
9.4.2 EE Mediating the Effects of Individual Factors on Feasibility and Desirability ....... 233
9.5 Conclusions ................................................................................................................ 240
vii
CHAPTER 10: CONCLUSIONS AND RECOMMENDATIONS ......................................... 242
10.0 Introduction ............................................................................................................... 242
10.1 Findings and Conclusions of the Research ............................................................... 242
10.2 Contributions to Knowledge ...................................................................................... 248
10.3 Implications to Policy and Practice ............................................................................ 254
10.4 Limitations and Recommendations for Future Research ........................................... 257
10.5 Final Conclusion ....................................................................................................... 260
REFERENCES ................................................................................................................. 262
APPENDICES .................................................................................................................. 290
viii
List of Appendices
Appendix 2.1 - Map of Zambia in the Context of Africa .............................................................. 290
Appendix 7.1 - Ethical Approval Notification- Interviews ............................................................ 291
Appendix 7.2 - Ethical Approval Notification-Survey .................................................................. 292
Appendix 7.3 - Letter of Introduction to Vice Chancellors at Zambian Universities ............... 293
Appendix 7.4 - Interview Questionnaire ........................................................................................ 294
Appendix 7.5 - Survey Questionnaire ........................................................................................... 297
Appendix 9.1 - Cross Tabulation of Age Groups by University Type ....................................... 303
Appendix 9.2 - ANOVA Tests on Age Differences in EI and Attitudes .................................... 303
Appendix 9.3 - Means and Standard Deviations for Age groups and EI ................................. 303
Appendix 9.4 - Post-Hoc Tests on EI Differences across Age Groups ................................... 304
Appendix 9.5 - Post-Hoc Tests for Differences in Employment and Self-Employment
Experience Across Age Groups ......................................................................... 304
Appendix 9.6 - EE Mediating the Influence of Normative Institution on Desirability .............. 305
Appendix 9.7 - EE Mediating the Influence of Cognitive Institution on Feasibility ................. 305
Appendix 9.8 - EE Mediating the Influence of Cognitive Institution on Desirability................ 305
Appendix 9.9 - EE Mediating the Influence of Regulatory Institution on Feasibility ............... 306
Appendix 9.10 - EE Mediating the Influence of Regulatory Institution on Desirability ........... 306
Appendix 9.11 - EE Mediating the Influence of Risk Taking Propensity on Feasibility ......... 306
Appendix 9.12 - EE Mediating the Influence of Risk Taking Propensity on Desirability ....... 307
Appendix 9.13 - EE Mediating the Influence of Locus of Control on Feasibility ..................... 307
Appendix 9.14 - EE Mediating the Influence of Locus of Control on Desirability ................... 307
Appendix 9.15 - EE Mediating the Influence of Need for Achievement on Feasibility .......... 308
Appendix 9.16 - EE Mediating the Influence of Need for Achievement on Desirability ......... 308
Appendix 9.17 - EE Mediating the Effect of Prior Entrepreneurial Exposure on Feasibility . 308
Appendix 9.18 - EE Mediating the Effect of Prior Entrepreneurial Exposure on Desirability 309
Appendix 9.19 - GEM Data on EI and Gain on EI from EE ....................................................... 309
Appendix 9.20 - GEM & World Bank Entrepreneurship and Ease of Doing Business Rank 309
Appendix 10.1- List of Empirical Studies Reviewed on Determinants of EI and Outcomes 310
ix
List of Figures
Figure 3.1 - Behaviour (B), Cognition (C) and Environment (E) Interaction ........................ 58
Figure 3.2 - The Process of Entrepreneurship (Shane, 2003) ............................................ 64
Figure 4.1 - Contexts of Intentionality Model ...................................................................... 70
Figure 4.2 - Revised Model for Contexts of Intentionality ................................................... 71
Figure 4.3 - Theory of Planned Behaviour Model ............................................................... 73
Figure 4.4 - Shapero and Sokol’s Entrepreneurial Event Model ......................................... 75
Figure 5.1 - Education and the Changing World ................................................................ 83
Figure 6.1 - Luethje and Franke (2003) Entrepreneurial Intention Model .......................... 106
Figure 6.2 - Hypothesised Model for the Mediating Role of EE ....................................... 106
Figure 7.1 – Saunders et al.’s (2012) Research Design Elements .................................... 131
Figure 7.2 - Framework of the Research and Methodology ............................................... 146
Figure 8.1 - Overview of Qualitative Research Findings on Determinants of EI ................ 207
Figure 9.1 - Quantitatively Tested Model for the Intervening Role of EE .......................... 212
Figure 9.2 - The Concept of Mediation .............................................................................. 224
Figure 10.1 – Validated Conceptual Model for the Mediating Role of EE .......................... 251
x
List of Tables
Table 2.1a - Zambian Population by Region ..................................................................... 11
Table 2.1b - Chronology of Zambian History ..................................................................... 12
Table 2.1c - Zambian Population by Ethnolinguistic Community ...................................... 13
Table 2.1d - Zambian Population by Religion .................................................................... 16
Table 2.1e - Zambia’s GDP Annual Growth Rate 2004 to 2014 ........................................ 17
Table 2.1f - Structure of Zambia’s Economy in 2013 .......................................................... 20
Table 2.2 - Unemployment Challenges in Zambia ............................................................. 25
Table 2.3 - Comparative Ease of Starting and Doing Business in Zambia.......................... 30
Table 2.4 - GEM Comparative Data on Entrepreneurial Activity in Zambia ....................... 32
Table 3.1 - Classification of Entrepreneurial Characteristics .............................................. 50
Table 5.1 - Entrepreneurial Behaviours, Attributes, Skills, Values and Beliefs ................... 86
Table 5.2 - Entrepreneurship Education Effectiveness Evaluation Framework ................... 95
Table 7.1a - Survey Sample Selection Procedure ............................................................ 149
Table 7.1b - Profiles of Interview Participants .................................................................. 151
Table 7.2 - Profile of the Sample of Final Year University Students ................................. 155
Table 7.3 - One-Sample T-test for Age Comparison with Student Population .................. 156
Table 7.4 - Items on EI and its Attitudinal Antecedents .................................................... 161
Table 7.5 - Items on Institutional Factors ......................................................................... 161
Table 7.6 - Items on Individual Factors ............................................................................ 162
Table 7.7 - Items on Effectiveness of EE ......................................................................... 163
Table 7.8 - Item and Cross-Loadings for Attitudinal Antecedents of EI ............................. 165
Table 7.9 - Item and Cross-Loadings for Institutional Factors .......................................... 166
Table 7.10 - Item and Cross-Loadings for Individual Factors ........................................... 167
Table 7.11 - Item and Cross-Loadings for Effectiveness of EE ......................................... 168
Table 7.12 - Reliability Analyses of Attitudinal Antecedents and EI ................................... 169
Table 7.13 - Reliability Analyses for Institutional Factors .................................................. 170
Table 7.14 - Reliability Analyses for Individual Factors ..................................................... 171
Table 7.15 - Reliability Analyses of Effectiveness of EE.................................................... 171
xi
Table 8.1 - Comparative Ease of Starting and Doing Business in Zambia........................ 179
Table 9.1a - Correlations among all Variables .................................................................. 211
Table 9.1b - Regression Coefficients’ Signs .................................................................... 214
Table 9.2 - Regression Analyses for Attitudinal Antecedents’ Influences on EI ............... 215
Table 9.3 - Regression Analyses for Influences on Feasibility .......................................... 216
Table 9.4 - Regression Analyses for Influences on Desirability ........................................ 219
Table 9.5 - Statistical Mediation Analyses Procedures ...................................................... 225
Table 9.6 - EE Mediating the Influence of Normative Institution on Feasibility .................. 228
Table 9.7 - Summary of Results for EE Mediating Institutional Factors’ Effects on Attitudes229
Table 9.8 - Summary of Results for EE Mediating Individual Factors’ Effects on Attitudes 234
Table 10.1 - Results of Hypotheses Testing ...................................................................... 245
xii
List of Abbreviations and Acronyms
ANOVA Analysis of Variance
ATB Attitude Toward the Behaviour
AU African Union
BI Business Incubator
BIS Department of Business Innovation and Skills (UK)
BoZ Bank of Zambia
BTS Bartlett’s Test of Sphericity
CABI Canadian Business Incubation Association
CBI Confederation of Business and Industry
CEEC Citizens Economic Empowerment Commission
CMB Common Methods Bias
CR Critical Realism
CSO Central Statistical office (Zambia)
DI Desire for Independence
EC European Commission
EE Entrepreneurship Education
EI Entrepreneurial Intention
ESE Entrepreneurial Self-Efficacy
EU European Union
GATE Growing America Through Enterprise
GDP Gross Domestic Product
GEM Global Entrepreneurship Monitor
GSE Generalised Self-Efficacy
HEIF Higher Education Innovation Fund
IAR Interaction and Access to Resources
ICMM International Council on Mining and Metals
ILC Internal Locus of Control
ILO International Labour Organisation
IMF International Monetary Fund
KMO Kaiser-Meyer-Olkin measure
LC Locus of Control
MSMEs Micro, Small and Medium-sized Enterprises
NAch Need for Achievement
NBIA National Business Incubation Association
NGO Non-Government Organisation
NI Normative Instititution
NTE Non-Traditional Exports
NTBC National Technology Business Centre
xiii
NUS National Union of Students
OECD Organisation for Economic Cooperation and Development
PA Personal Attitude
PBC Perceived Behavioural Control
PCA Principal Component Analysis
PEE Prior Entrepreneurial Exposure
PI/EL Practical Involvement in Entrepeneurship/Experiential Learning
PLS Perceived Learning and Skills acquired from the Module/Programme
QAA Quality Assurance Authority (UK)
RTP Risk Taking Propensity
SARUA Southern African Regional Universities Association
SCT Social Cognitive Theory
SEE Shapero’s Entrepreneurial Event Model
SEM Structural Equation Modelling
SLT Social Learning Theory
SMEs Small and Medium-sized Enterprises
SN Subjective Norms
SPEED Student Placement for Entrepreneurs in Education
SPSS Statistical Package for Social Sciences Version 20
TEA Total Early Entrepreneurial Activity
TPB Theory of Planned Behaviour
UoW University of Wolverhampton
UWBS University of Wolverhampton Business School
UK United Kingdom
UNCTAD United Nations Conference for Trade and Development
UNESCO United Nations Education, Scientific and Cultural Organisation
US/USA United States of America
VIF Variance Inflation Factor
WB World Bank
WEF World Economic Forum
ZDA Zambia Development Agency
xiv
List of Key Definitions
Entrepreneurship Entrepreneurship is a process that involves the recognition, evaluation and exploitation of
opportunities to meet market needs (by introducing new products or processes, access to
new markets or raw materials) through organising efforts that previously had not existed.
Graduate Entrepreneurship Graduate entrepreneurship is concerned with the extent to which graduates as products of
university/college education engage in new venture creation or self-employment.
Intention Intention is an indication of how hard an individual is willing to try, of how much of an effort
he or she is planning to exert, in order to perform a behaviour.
Entrepreneurial intention Entrepreneurial intention is a self-acknowledged conviction of a person who intends to
start a business and consciously plans to do so at a certain point in future.
Perceived Desirability Perceived desirability of entrepreneurship refers to the degree to which an individual finds
starting and managing one’s own business attractive i.e. the eagerness a person
demonstrates to start a business.
Perceived Feasibility Perceived feasibility of entrepreneurship is the degree to which one believes that not only
is he/she personally capable of starting and managing a business but that
entrepreneurship is a viable undertaking.
Enterprise Education Enterprise education is concerned with developing “an enterprising way of thinking and a
way of doing” in students. It is a pedagogical approach that involves creative idea
generation, development and implementation. This approach helps to develop
enterprising attitudes, skills and behaviours which can be applied in the world of work in
any field.
Entrepreneurship Education Entrepreneurship education is the transfer of knowledge and skills about how to create,
manage and grow a business.
Effectiveness of Entrepreneurship Education Effectiveness of entrepreneurship education referes to the level of entrepreneurship
knowledge and skills students acquire through entrepreneurship education.
Environmental Institutions on Entrepreneurship Institutions comprise the relevant factors in the environment that provide formal and
informal rules and norms that either restrict or facilitate entrepreneurial behaviour.
xv
Regulatory institutions include favourable laws and regulations for business
formation and operations as well as mechanisms supportive of individuals’
entrepreneurial efforts.
Cognitive institutions refer to the level of shared knowledge and information in
society about venture creation, operations and growth.
Normative institutions refer to acceptability and admiration of innovation, creativity
and entrepreneurial careers in society.
1
CHAPTER 1: INTRODUCTION TO THE RESEARCH
1.1 Outline of the Research Project
Entrepreneurship involves identifying, evaluating, and exploiting opportunities and
introducing new products to the market through organised efforts (Carree and
Thurik, 2010; Kirzner, 1997; Knight, 1921; Miller, 1983; Schumpeter and
Backhaus, 1934; Shane, 2003). There is a general recognition that
entrepreneurship contributes to economic development, competition, innovation
and employment generation in economies (de Kok and de Wit, 2014; Hessels and
van Stel, 2011; Neumark et al., 2011; Peters, 2014; Pickernell et al., 2011;
Wennekers et al., 2005). For instance, in Zambia, micro, small and medium-sized
enterprises (MSMEs) account for 97% of all firms and contribute 89% of the jobs in
the economy (CSO, 2011a; CSO, 2011b; CSO, 2013). In developed countries like
the United Kingdom, MSMEs account for 99.9% of all enterprises, 58.8 % of
private sector employment and 48.8% of private sector turnover (Lord Young,
2012).
Given the potential benefits in relation to entrepreneurship (Gray, 2006), there is
increasing expectation that entrepreneurship addresses the unemployment
challenges faced by young university graduates (Henry, 2013). On the one hand,
as technology and contingent factors are changing, the expectations of employers
are shifting and they increasingly demand for graduates who possess enterprising
or entrepreneurial attributes to help them develop competitive advantage (CBI -
NUS, 2011; Collins et al., 2004b; Galloway et al., 2005; Mitra, 2011; Wilson et al.,
2009). Competition for jobs is becoming intense, therefore, students need to
proactively develop appropriate skills to align with the changing job market
(Woodier-Harris, 2010). On the other hand, university education is no longer a
Introduction
2
passport to secure employment for the 21st century graduate (Collins et al., 2004b;
Nabi and Bagley, 1999). Globally, the number of new graduates is increasing while
available jobs are fewer, compelling stakeholders to consider initiatives that
promote new venture creation as a viable career option (Culkin, 2013; Nabi and
Holden, 2008). Thus, understanding factors that promote graduates’ involvement
in entrepreneurship becomes vital (Nabi and Liñán, 2011).
Policy makers, researchers and practitioners increasingly recognise the significant
role that higher education plays in nurturing enterprising graduates and graduate
entrepreneurs (Harrison and Leitch, 2010; Herrmann et al., 2008). The World
Economic Forum (WEF) suggests that considering the power that education has in
developing skills and attitudes as well as generating an entrepreneurial mind-set, it
becomes clear that entrepreneurship education (EE) is important (Wilson et al.,
2009). Researchers argue that the purpose of EE is mainly threefold (Blenker et
al., 2011; Gibb, 2007; Packham et al., 2010; Rae et al., 2012; Solomon et al.,
2002):
a) To develop an entrepreneurial mind-set and enterprising skills including
creativity, innovativeness, problem solving, opportunity identification,
opportunity evaluation, leadership and proactive action in responding to
changes;
b) To build up a wide understanding of entrepreneurship and its application to
a diversity of settings; and
c) To develop capabilities and confidence to start, operate and grow an
enterprise effectively.
Introduction
3
1.1.1 Rationale of the Study and Research Problems
An established body of studies suggests that the intention to start a venture is
critical to entrepreneurship (Bird, 1988; Krueger JR et al., 2000; Liñán et al.,
2011a; Shinnar et al., 2012). Entrepreneurial intention (EI) is a self-acknowledged
conviction of a person who intends to start a business and consciously plans to do
so at a certain point (Forbes, 1999; Katz, 1992; Learned, 1992; Rotefoss and
Kolvereid, 2005; Thompson, 2009). The Global Entrepreneurship Monitor (GEM)
finds that EI is an important indicator of entrepreneurship in a society (Kelley et al.,
2012). This is because individuals with high EI are more likely to start a business
than those with low EI (Matlay, 2008; Ajzen, 2002; Henley, 2007). Thus,
understanding EI is important for understanding entrepreneurial behaviour (Shane
and Venkataraman, 2000). Based on the works of Shapero and Sokol (1982) and
Ajzen (1991), EI is parsimoniously a function of perceived desirability (i.e. ‘is it a
good thing for me to do?’) and perceived feasibility, (i.e. ‘could I do it if I wanted
to?’). However, scholars indicate that there is little knowledge about determinants
of perceived feasibility and desirability of entrepreneurship (Hindle, 2009;
Davidsson, 2004; Schlaegel and Koenig, 2014).
In exploring the determinants of EI, prior studies investigate individual factors,
contextual factors and EE in isolation from each other (Shook, et al., 2003; Fayolle
and Liñán, 2014). Further, there are a number of issues identified in the literature:
First, studies on the relationship between EE and EI have yielded mixed and
inconsistent conclusions (Bae et al., 2014; Küttim et al., 2014; Williamson et al.,
2013). Some studies find that EE has a positive impact on EI (Farashah, 2013;
Matlay, 2008; Peterman and Kennedy, 2003; Solesvik et al., 2013; Souitaris et al.,
2007; Wilson et al., 2007; Zhang et al., 2013; Zhao et al., 2005) whilst others
observe that EE has either no discernible influence or a negative influence on EI
(Cox et al., 2002; do Paço et al., 2013; Marques et al., 2012; Oosterbeek et al.,
Introduction
4
2010; Packham et al., 2010; Tegtmeir, 2012; von Graevenitz et al., 2010; Walter et
al., 2011). The inconsistent findings have prompted scholars to suggest that since
EE and business start-up support by government and other stakeholders are
investments, empirical research is required to clarify how these initiatives impact
EI (Nabi et al., 2010; Rae et al., 2012).
Second, there is a shortage of studies examining the effect of institutional factors
on EI. Few existing studies have investigated the effects of institutions on the rate
and type of entrepreneurial activity in a country based on institutional theory.
However, studies investigating the effects of institutions at micro-level, i.e.
individual cognition and behaviour, are rare (Bruton et al., 2010; De Clercq et al.,
2011; Schlaegel and Koenig, 2014; Wicks, 2001). Fayolle and Liñán (2014) argue
that “future research should also assess the impact of culture, regulatory systems
and legal policies on intentions” (p.664). Similarly, Schlaegel and Koenig (2014)
claim “it is meaningful for future research to further explore the contingent roles of
the formal institutional context (laws, regulations, and policies) as well as the
informal institutional context (culture, norms and values)…to offer great insights
into the context-specific development of EI” (p.320).
Third, there is a shortage of studies investigating the combined effect of EE,
individual and contextual factors on EI (Fayolle and Liñán, 2014; Rideout and
Gray, 2013; Solesvik et al., 2013; Wang and Chugh, 2014). Moreover, the extant
literature indicates a lack of research proposing and validating integrated models
in relation to determinants of EI (Fayolle and Liñán, 2014; Krueger, 2009; Shook et
al., 2003). This limits understanding of the interplay among various EI
determinants. The following quotes evidence this hitch in the EI literature:
“With regard to theoretical limitations, the EI literature has not resulted in cumulative knowledge because the various perspectives have been pursued in isolation from other perspectives. Future work on EI should
Introduction
5
attempt to integrate and reduce the number of alternative models.” Shook et al. (2003, p.386)
“(on the future of entrepreneurial intention research)…as Krueger (2009) suggests, the construct of intentions appears to be deeply fundamental to human decision making, and as such, it should afford us multiple fruitful opportunities to explore the connection between intent and a vast array of other theories and models that relate to decision making under risk and uncertainty. This view opens the door for the development of integrative and more sophisticated theoretical models of the entrepreneurial process…New research may consider interaction…moderation…and mediation effects.” Fayolle and Liñán (2014, p.664)
Lastly, the literature also shows that research on the determinants of EI is mainly
conducted in developed countries (Audretsch, 2007; Bruton et al., 2010; Fayolle
and Liñán, 2014; Hoskisson et al., 2011; Iakovleva et al., 2011; Nabi and Liñán,
2011). One way to develop an in-depth understanding of EI is to execute studies in
a diversity of national contexts.
In response to the identified issues in the extant literature, this study seeks to
examine the determinants of EI at individual and institutional levels. Additionally,
the study seeks to explore whether EE affects the relationships between individual
and institutional factors and EI. There are two reasons for this investigation. Firstly,
EI is incorporated in many studies even when the research coverage has not been
extended to EE (BarNir et al., 2011; Birdthistle, 2008; Davey et al., 2011;
Levenburg et al., 2006; Wu and Wu, 2008). For instance, Franke and Luethje
(2003) find that environmental and individual factors are positively associated with
EI. It is worthwhile to explore the role EE plays in this process. Secondly, based
on reviews of extant literature, scholars indicate the need to explore if, why and
how EE’s impact may differ in different learning contexts and with different
individuals (Rideout and Gray, 2013; Wang and Hugh, 2014; Cope, 2005; Fairlie
and Holleran, 2011). It would be enlightening to study EE and its interaction with
contextual and individual factors.
Introduction
6
1.1.2 Aims and Objectives of the Study
Based on the literature review, and having EE as the kernel, this study aims to a)
examine individual and institutional determinants of EI; and b) explore the effect of
EE on the relationships between the above determinants and EI. Specifically, the
current research’s objectives are:
To examine the influence of institutional factors on entrepreneurial intention;
To investigate the influence of individual factors on entrepreneurial
intention; and
To explore and examine if entrepreneurship education has an intervening
role on the effects of institutional and individual factors on entrepreneurial
intention.
1.2 Contributions to Knowledge
This study has four major contributions to the field. The first and most important
contribution relates to the effect of EE on EI. The extant literature has mixed
conclusions; while some studies find that EE has positive effects on EI, others
report negative effects. This study contributes to knowledge by establishing that
the effect of EE on EI should be evaluated in conjunction with factors at individual
and institutional levels. The study demonstrates that effectiveness of EE
significantly mediates the effect of individual and institutional factors on perceived
feasibility and desirability of entrepreneurship. This means that individual and
institutional factors influence the uptake, interest, effort and the consequent
performance in EE to develop entrepreneurship knowledge and skills.
Entrepreneurship knowledge and skills in turn influence the perception that
starting, managing and growing a business is feasible and desirable. This
ultimately leads to EI.
Introduction
7
Secondly, scholars indicate that research on the influence of EE, individual and
contextual factors on EI has grown in isolation from each other. This has prompted
calls for integrated models that help to examine how factors from the three angles
are related in shaping EI. Scholars have argued that focusing on only one angle
often leads to incomplete understanding and sometimes inconsistent conclusions.
The current study contributes to knowledge by developing and empirically
validating a multi-level conceptual framework about the effect of EE on the
relationships between EI and its institutional and individual determinants.This
integrated model is unlike many prior studies and models that focus on one or two
sets of factors. The current research has identified that effectiveness of EE
comprises perceived learning from the module, experiential learning and utilisation
of resources. Individual factors consist of risk taking propensity, locus of control,
need for achievement, and prior entrepreneurial exposure. Lastly, institutional
factors comprise normative, cognitive and regulatory institutions. The validated
integrated model shows that individual and institutional factors are the primary
predictors of perceived feasibility and desirability of entrepreneurship. The role of
EE is to mediate these relationships. This means that individual and institutional
factors exert their effects on EI not only through their influence on perceived
feasibility and desirability but also through their influence on effectiveness of EE.
By developing entrepreneurial capabilities and clarifying the benefits of
entrepreneurship, EE enhances perceptions that business start-up is feasible and
desirable. This ultimately leads to EI.
Thirdly, scholars indicate that generally most studies in entrepreneurship, graduate
entrepreneurship and EI in particular, are conducted in developed countries, which
limits the generalisability of research findings. The consequence of scant research
in developing countries is that researchers, policy makers, educators and other
Introduction
8
stakeholders do not have adequate information that takes into account local
contexts for research, practice and policy direction. By conducting the research in
Zambia, the study confirms the applicability of the basic EI model as well as the
influences of institutional factors, individual factors and EE on EI in a developing
country context.
The last contribution is the further development and validation of the constructs of
effectiveness of EE. Extant literature indicates that the link between pedagogical
approaches and EI is not clear. Rideout and Gray (2013) indicate that “clearly
there is also need for development of pyschometrically sound measures to support
efforts in…entrepreneurship education research” (p.348). In the literature, only
Souitaris et al. (2007) developed and validated constructs of effectiveness of EE,
including dimensions of perceived learning and utilisation of resources. The
present study expanded the constructs by containing perceived experiential
learning (practical approaches). This allows the measurement of effectiveness of
EE to go beyond the education content (i.e. learning from the module) and
embrace experiential learning (i.e. learning by doing). This is important because
EE delivery is widely criticised for being dominated by lectures and seminars; EE
delivery should include experiential learning to be relevant and practical. Practical
approaches to delivery of EE are positively assocated with EI and its attitiudinal
antecedents.
1.3 Summary of the Thesis Contents
This thesis comprises ten chapters including the introduction. A general summary
of the content of each of these chapters is provided here.
Chapter 2 - discusses Zambia’s history and economy as a context for the current
research. Specifically, it discusses the structure of the Zambian economy and its
Introduction
9
challenges. It also covers the institutional framework that supports business start-
up and SMEs. Lastly, it highlights graduate unemployment, graduate
entrepreneurship, and the status of EE in higher education in Zambia.
Chapter 3 - reviews literature by providing a historical and theoretical overview of
entrepreneurship. Specifically, it highlights the classical, psychological and
sociological theoretical approaches to understanding the role and determinants of
entrepreneurship. Lastly, it highlights the processes and stages of
entrepreneurship.
Chapter 4 - reviews literature on the role of EI in the entrepreneurial process and
shows the evolution of the EI models. Specifically, it focuses on the theory of
planned behaviour, Shapero’s entrepreneurial event model, and social cognitive
theory as the foundation for understanding EI and its determinants.
Chapter 5 - reviews literature on the nature, importance and effects of EE on EI. It
highlights the global pressures moulding the need for more entrepreneurship in
society. Then it discusses the nature as well as types of enterprise and
entrepreneurship education.
Chapter 6 - develops the conceptual model and hypotheses to examine a) the
effects of institutional factors on perceived feasibility and desirability of
entrepreneurship, b) the effects of individual factors on perceived feasibility and
desirability, c) the intervening role of EE on the effects of individual and
institutional factors on perceived feasibility and desirability, and d) the effects of
perceived feasibility and desirability on EI.
Chapter 7 – focuses on the justification and implementation for the adopted
research design. It discusses the population, sampling and data collection
procedures; analyses validity and reliability of quantitative research measures;
Introduction
10
and, inspects common methods bias. To avoid bias from utilising one particular
methodology, this study purposely employed a concurrent triangulation strategy.
This was intended for model testing and in-depth understanding of research
phenomena.
Chapter 8 - synthesises results of semi-structured interviews in Zambia. The
findings of the interviews are discussed in relation to existing literature. Lastly, it
explains the implications of the evidence on the conceptual model.
Chapter 9 - quantitatively examines the effects of individual and institutional
factors on EI. It then reports and discusses results on how EE mediates the effects
of individual and institutional factors on EI. The findings of the survey are
discussed in relation to qualitative results and existing literature.
Chapter 10 - highlights the major research findings and conclusions, contributions
to knowledge as well as implications to policies and practices. It also analyses the
limitations of the current study and on this basis recommends future research
directions.
11
CHAPTER 2: RESEARCH BACKGROUND - ZAMBIAN CONTEXT
2.0 Introduction
The preceding chapter provides an overall introduction, objectives and scope of
the current research. The study aims to investigate the effects of entrepreneurship
education (EE) on the relationships between entrepreneurial intention (EI) and its
determinants. Most studies on the determinants of EI are conducted in developed
countries, and this limits the generalisability of findings elsewhere (Bruton et al.,
2010; Fayolle and Liñán, 2014; Hoskisson et al., 2011; Nabi and Liñán, 2011).
This chapter on the Zambian context highlights the history of the country and its
culture, the structure of the economy and its challenges, youth and graduate
unemployment, as well as the status of EE in higher education.
2.1 Zambian History and Culture
According to the Central Statistical Office (CSO), Zambia has a population of
13.092 million people, 2.8% population annual growth rate and a population
density of 17.4 per square kilometre (CSO, 2013). As indicated in Table 2.1a,
about 60% of its population are based in the rural areas and 40% in the urban
areas. These proportions have remained stable over the last 10 years.
Table 2.1a - Zambian Population by Region
With a total area of 752,614 square kilometres, Zambia is a landlocked country in
central southern Africa. It shares its borders with eight other countries (see map in
Appendix 2.1). As indicated in Table 2.1b, Zambia used to be a British colony until
Total Rural Urban
2000 9,885,591 (100%) 6,458,729 (65.3%) 3,426,862 (34.7%)
2010 13,092,666 (100%) 7,919,216 (60.5%) 5,173,450 (39.5%)
Source: (CSO 2013) 2000 and 2010 Population Censuses
Census YearPopulation by Region
Research Background
12
October 1964 when it became independent. With a largely tropical climate, the
country has vast arable land, mineral and water resources. From about 1970 to
1991, Zambia pursued socialist economic policies through which most economic
activities were undertaken by the state. Since 1992, the country started to adopt
open market policies.
Table 2.1b - Chronology of Zambian History
Ethnicity, Culture and Religion in Zambia Zambia stands out in Africa as one of the most peaceful countries. In its early
years as an independent state, Zambia became a regional bulwark against
imperialism and colonial domination. Today, it is looked upon as an important
example of Africa’s democratisation with both incredible success as well as some
Era Period, Year Major Events in the History of Zambia
Pre-Colonial 1100 Bantu migration displaces indigenous San peoples.
1200 Tonga and Ila peoples migrate from the east.
1500s–1750 Fragments of the Luba and Lunda empires in
Congo migrate to Zambia, forming new kingdoms;
the Bemba, Bisa, Lovale, Kaonde, Lamba, Lunda,
and Lozi emerge.
1851 First visit to area by the Scottish missionary and
explorer David Livingstone.
Colonial 1889–90 British South Africa Company (BSA) establishes
control over Northern Rhodesia (present day Zambia)
1924 BSA cedes control over Northern Rhodesia to
British Colonial Office.
1953–63 Federation is established among three colonial territories
of Northern Rhodesia (Present day Zambia), Southern Rhodesia (Present day
Zimbabwe) and Nyasaland (present day Malawi)
1962 Civil disobedience accelerates moves toward independence
Independence 1964, October 24 Independence (Northern Rhodesia becomes Zambia)
One Party State & 1972, December One Party Declaration is enacted ( 2nd Republic, largely Socialist economic agenda)
Socialist Agenda mid 1970s -1980s Copper prices plunge; high oil prices; and national debt increases.
1985 Zambia adopts comprehensive economic (structural) adjustment
program (SAP) with International Monetary Fund and the World Bank
1986–87 Food shortage riots.
1987, May The Structural Adjustment Program (SAP) is
abandoned unilaterally by Zambia.
1989, June New SAP is initiated; abolishes price controls,
except on staples
1990, June Food shortage riots.
1990, June Reports of an attempted coup against Kaunda
precipitate widespread public celebration.
1990, July Movement for Multiparty Democracy (MMD)
coalition is established.
Multipartism 1990, December Parliament approves multiparty option (Third Republic Begins).
1991, June Reintroduction of price controls by the United
National Independence Party (UNIP) weakens SAP
1991, September Adjustment programme is suspended again
Free Market Economy 1991, October 31 MMD wins, and Frederick Chiluba is elected
Consolidation president (Consolidation of free market economy begins)
Adapted from: Taylor D.S (2006), Culture and Customs of Zambia, Greenwood Press,Westport, USA, p.xv
Research Background
13
notable setbacks. The country is also one of the most urbanised in sub-Saharan
Africa, a phenomenon that began with the colonial era gravitation toward the
central mining regions of Zambia’s Copperbelt. As a result of this urban influx,
Zambia’s diverse ethnolinguistic groups (73 major ethno-linguistic communities as
indicated in Table 2.1c) interact regularly. Moreover, many contemporary Zambian
households, especially those in cities, are also exposed to western cultures via the
media. In other words, notions of tradition and modernity combine in interesting
ways in contemporary Zambia (Taylor, 2006).
Table 2.1c - Zambian Population by Ethnolinguistic Community
National culture consists of the underlying value systems that are specific to a
group or society and motivate individuals to behave in certain ways (Hofstede,
1984; Hofstede, 2014). Hofstede’s seminal cross-cultural comparison shows six
dimensions of cultures: individualism, uncertainty avoidance, power distance,
masculinity, pragmatism and indulgence (Busenitz and Lau, 1996; Shinnar et al.,
2012). Hofstede (2014) evaluates each country’s culture based on a scale of 1
(lowest) to 100 (highest) on each of the six dimensions. A score of 50 on any
dimension means that such a country is difficult to classify with respect to that
dimension (Shinar et al., 2012; Siu and Lo, 2013). Busenitz and Lau (1996) and
Shinnar et al. (2012) suggest that individualistic, masculine cultures ranking high
on power distance and low on uncertainty avoidance would create favourable
environments for entrepreneurship and potentially lead to a higher proportion of
self-employment.
Ethnolinguistic Groups Population by Ethnicity Percent
Black Zambians - 73 tribes/dialects 12,870,814 98.3%
Other Black Africans 202,348 1.5%
Whites (mainly British, American and Other Europeans) 7,898 0.06%
Asian (mainly Indians, Chinese) 11,606 0.09%
Totals 13,092,666 100.0%
Source: (CSO) 2010 Census of Population and Housing
Research Background
14
In relation to Zambia, the score on the individualism dimension is 35, reflecting a
collectivistic society1 (Hofstede, 2014). This means that people have long-term
commitment to the groups they belong to. These groups may be immediate and
extended family; they could also be other extended social and organisational
relationships. Loyalty in a collectivist culture is paramount, and overrides most
other societal rules and regulations. This means that the approval or dispproval of
family, friends and others is crucial to decision-making. Scholars indicate that
emphasis on group comformity may be negatively associated with rates of
entrepreneurship (Hofstede, 1984; Shinnar et al., 2012).
Second, with a score of 40 on the dimension of masculinity, Zambia is considered
as a feminine2 society (Hofstede, 2014). In feminine countries the focus is on
“working in order to live”. Managers strive for consensus, while people value
equality, solidarity and quality in their working lives. Scholars indicate that such
societies are likely to have low rates of entrepreneurship (Shinnar et al., 2012).
This is because the focus is more on wellbeing and less on achievement and
success.
1 Individualism as a cultural dimension addresses the degree of interdependence a society
maintains among its members. It has to do with whether people’s self-image is defined in terms of “I” or “We”. In individualist societies people are supposed to look after themselves and their direct family only. In collectivist societies, people belong to ‘in groups’ that take care of them in exchange for loyalty; individual autonomy and interest are valued less.
2 With respect to masculinity, a high score indicates that the society will be driven by competition,
achievement and success, with success being defined by the winner/best in field – a value system that starts in school and continues throughout organisational behaviour. A low score (feminine) means that the dominant values in society are caring for others and quality of life. A feminine society is one where quality of life is the sign of success and standing out from the crowd is not admirable. The fundamental issue here is what motivates people, wanting to be the best (masculine) or liking what you do (feminine).
Research Background
15
Third, Zambia scores at an intermediate level on the dimension of power distance3
(score of 60), which means that it has a hierarchical society (Hofstede, 2014).
Hierarchy in society and organisations is seen as reflecting accepted inherent
inequalities, centralisation in popular, subordinates expecting to be told what to do
and the ideal boss being a benevolent autocrat. Scholars indicate that the powerful
individuals in such societies are more likely to have high confidence and
willingness for start-up (Busenitz and Lau, 1996).
Fourth, Zambia scores an intermediate 50 on the dimension of uncertainty
avoidance4. This means that no generalisation can be made about whether or not
the society has a tendency to embrace or shun courses of action that involve
uncertainty, risk taking and innovation (Hofstede, 2014; Shinnar et al., 2012). Fifth,
a low score of 30 on the pragmatism dimension means that Zambian culture is
more normative than pragmatic5 (Hofstede, 2014). People in such societies have a
strong concern with establishing the absolute truth; they are normative in their
3 Power distance is a dimension that deals with the fact that all individuals in societies are not equal
– it expresses the attitude of the culture towards these inequalities. Power distance is defined as the extent to which the less powerful members of institutions and organisations within a country expect and accept that power is distributed unequally. 4 Uncertainty Avoidance is a dimension concerned with how a society deals with the fact that the
future can never be known: should one try to control the future or just let it happen? This ambiguity brings with it anxiety and different cultures have learnt to deal with this anxiety in different ways. The extent to which the members of a culture feel threatened by ambiguous or unknown situations and have created beliefs and institutions that try to avoid these is reflected in the uncertainty avoidance score.
5 Pragmatism describes how every society has to maintain some links with its own past while
dealing with the challenges of the present and future, and societies prioritise these two existential goals differently. Normative societies who score low on this dimension, for example, prefer to maintain time honoured traditions and norms while viewing societal change with suspicion. Those with a culture which scores high, on the other hand, take a more pragmatic approach: they
encourage thrift and efforts in modern education as a way to prepare for the future.
Research Background
16
thinking. They exhibit great respect to traditions and the propensity to achieve
short-term results.
Lastly, the relatively low score of 42 on the indulgence6 dimension indicates that
the Zambian culture can be classified as a restraint one (Hofstede, 2014). Such
societies have a tendency to be cynical and pessimistic. Also, in contrast to
indulgent societies, restrained societies do not put much emphasis on leisure time;
they control the gratification of their desires. People with this orientation have the
perception that their actions are restrained by social norms and feel that indulging
themselves is somewhat wrong.
Religion in Zambia
Zambia has a religiously plural environment that includes world religions, such as
Christianity, Islam and Hinduism (Taylor, 2006). The vast majority of its population,
however, practice various denominations of Christianity. Christianity arrived in the
country in the 1850s but did not establish a solid foothold until the early 1900s
when missionary activity proliferated in conjunction with the establishment of
colonial control over the territory.
Table 2.1d - Zambian Population by Religion
Source: CSO (2013)
6 Indulgence is concerned with the extent to which people try to control their desires and impulses,
based on the way they were raised. Relatively weak control is called “indulgence” and relatively
strong control is called “restraint”. Cultures can, therefore, be described as indulgent or restrained.
Description Catholic Protestant Muslim Hindu Buddist Bahai Faith Other None Total*
Number 2,532,858 9,436,231 61,412 4,383 9,623 3,891 253,621 224,295 12,526,314
Percent 20.2% 75.3% 0.5% 0.03% 0.1% 0.03% 2.0% 1.8% 100%
*Only Individuals above the age of 5 years are included
Research Background
17
As depicted in Table 2.1d, Christianity claims 95.5% of the population as
adherents (CSO, 2013). Therefore, although many of the traditional beliefs survive
(and may co-exist with Christianity), on the whole, protestant perspectives
influence attitudes to work and career in the majority of the population (Shinnar et
al., 2012).
2.2 Structure of Zambia’s Economy and Its Challenges
With an economy of US$22.38 billion in gross domestic product (GDP), Zambia
recorded GDP growth of 6.4 percent in 2013 from 2012 (Bank of Zambia, 2014;
World Bank, 2014). Over the medium to long term, agriculture, mining,
manufacturing, tourism, energy and construction are expected to be major drivers
of GDP growth and job creation (National Budget, 2014). Between 1961 and 2013,
the annual GDP growth rate averaged 2.9 percent; it reached an all-time high of
16.7 percent in 1965 and a record low of -8.6 percent in 1994. As depicted in
Table 2.1e, between 2004 and 2014, Zambia’s economy has grown more rapidly
due to expansion of the copper mining industry and diversification into the
agricultural sector.
Table 2.1e - Zambia GDP Annual Growth Rate 2004 to 2014
Source: (Bank of Zambia, 2014)
Research Background
18
However, the widespread poverty remains to be Zambia’s main economic
challenge (Chigunta, 2002; Chigunta et al., 2005; World Bank, 2013), primarily
because of fast population growth and youth unemployment. Consequently,
Zambia continues to be one of the poorest countries in the world with 60 percent
of the population living below the poverty line (World Bank, 2014).
Economic development consists of changes in the quantity and character of
economic value added (Lewis, 1954). These changes result in greater productivity
and increasing per capita incomes. They often coincide with migration of labour
across different economic sectors in the society. For instance, labour may migrate
from primary and extractive sectors to the manufacturing sector, and eventually,
services sector (Naudé et al., 2008). According to the GEM and the World
Economic Forum (WEF), predominant economic and entrepreneurial activities
may differ based on whether an economy is factor-driven, efficiency-driven or
innovation-driven (Kelley et al., 2012; Wilson et al., 2009).
The factor-driven economies are usually dominated by subsistence agriculture and
extraction businesses, with a heavy reliance on labour and natural resources
(Kelley et al., 2012). As extractive industries develop, this triggers economic
growth, prompting surplus population from agriculture to migrate toward extractive
and labour-intensive sectors, which are often located in specific regions. The
resulting oversupply of labour in those regions compels unemployed individuals to
start their own small businesses or engage in self-employment activities in order to
survive and make a living. The GEM (2012) survey notes that it is typical for factor-
driven economies to report higher proportions of informal (unregistered)
businesses; individuals are pushed into the entrepreneurship trajectory because
other options for work are absent i.e. engaging in self-employment is the only
means for livelihood and survival (Kelley et al., 2012; Williams, 2009).
Research Background
19
The efficiency-driven economies are characterised by industrialisation and reliance
on economies of scale, and the dominance of capital-intensive large organisations
(Acs and Szerb, 2012). Depending on how well developed the financial sector is,
such economies would also spur opportunities for development of small-scale and
medium-sized manufacturing enterprises, as part of the supply chain to service
large businesses (Hessels and van Stel, 2011). Thus, compared to factor-driven
economies, efficiency-driven economies usually have lower proportions of informal
(unregistered) businesses and higher proportions of small-scale manufacturing
and service sector firms (Kelley et al., 2012).
The innovation-driven economies have industrial activities characterised by
sophistication and variety as well as intensity in knowledge, research and
development. Such economies have a large contribution of the service sector to
GDP (Martinez et al., 2010). This is in response to the needs of an increasingly
affluent population; high demand for services is normally expected of a high-
income society. As long as financial and other institutions are able to
accommodate and support opportunity-seeking activities, innovative
entrepreneurial firms may emerge as significant drivers of economic growth. In this
way, entrepreneurial firms may also operate as ‘agents of creative destruction’
(Schumpeter and Backhaus, 1934; Schumpeter, 1934). Compared to factor-driven
and efficiency-driven economies, innovation-driven economies usually have lower
proportions of informal (unregistered) businesses and higher proportions of
knowledge intensive and service sector firms (Kelley et al., 2011). Additionally,
most entrepreneurs in innovation-driven economies are drawn into business start-
up not for survival but to exploit opportunities to increase their incomes or
independence (Gilad and Levine, 1986; Martínez et al., 2010; Orhan and Scott,
2001; Williams, 2009).
Research Background
20
Table 2.1f - Structure of Zambia’s Economy in 2013
Source: (African Economic Outlook, 2014; CSO, 2013; World Bank, 2014)
In light of the foregoing characteristics of economic and entrepreneurial activity,
Zambia’s economy should be categorised as factor-driven. This is because, as the
evidence in Table 2.1f shows, the primary sectors (mining and agriculture) have
the highest contribution of 74.5% to overall employment. Yet in relation to formal
employment, the CSO (2011) data indicates that agriculture and mining only
contribute 12.1% and 8.1%, respectively. This means that the majority of the
employment in agriculture is informal. In addition, the country is heavily dependent
on forex earnings from mining exports (75.2%). In relation to the composition of
firms in the economy, 90% operate informally i.e. they are not formally registered.
This has many implications. Firstly, informal firms do not make a contribution to
the government tax revenue. Secondly, informal enterprises do not make any
financial contributions to social security schemes. Thirdly, informal firms may not
employ individuals within the Law’s minimum requirements in terms of conditions
of work and service. Lastly, unregistered businesses lack the basis for developing
track records and, therefore, may not access banking services and other
opportunities. This constrains their growth in the economy (Calice et al., 2012; De
Soto, 2003; Gilbert, 2002; Tendler, 2002; Woodruff, 2001). No wonder, the
majority of individuals (78%) who start businesses in Zambia either use personal
savings or borrow funds from family members (Bank of Zambia FinScope, 2010).
From the forgoing discussion on the structure of the Zambian economy, there is
clearly a demand for formalised entrepreneurial activity. This would enable
Sectors Share of GDP Share of Employment
Agriculture (forestry, agric., fisheries, hunting) 19.5% 66.4%
Mining and Quarrying 10.0% 8.1%
Industry (construction and manufacturing) 27.3% 0.9%
Services 43.2% 24.6%
Totals 100.0% 100.0%
Research Background
21
capable entrepreneurs to harvest the benefits. Therefore, drivers of
entrepreneurial intention and activity at individual and institutional levels are to be
examined. This would enable scholars, policy makers and practitioners to
understand the role that different stakeholders can play in increasing formal
entrepreneurial activity (De Clercq et al., 2011; Gartner, 1989a; Hoskisson et al.,
2011; Rideout and Gray, 2013).
2.2.1 Diversification Efforts and Entrepreneurship
Despite the Zambian economy growing at an annual average of 6.1% in the last
10 years, there are many challenges. These include high unemployment, over
dependence on the mining sector for foreign exchange earnings (75.2%) and a
large informal sector (World Bank, 2013). The informal sector is largely composed
of micro and small businesses whose performance is undocumented. Therefore, in
the medium to long term, it is necessary to focus on mechanisms to increase
participation of Zambians in the formal economy. This resonates with an
observation by the Zambian Finance Minister in the quote below:
"…Alexander Chikwanda, Minister of Finance, said ‘…the economy has remained strong and stable. The Zambian economy’s growth is among the ten fastest in the world and among the four fastest in Sub-Saharan Africa… We need to intensify efforts aimed at enhancing Zambians' participation in the formal economy…in the long term, we will need to increase our resilience to shocks by accelerating the diversification of the economy away from copper to ensure resilience to global financial shocks…lack of significant participation of Zambians in the formal economy has resulted in the foreign exchange market being controlled by a cartel of foreign companies.’ ” (Quote from Sinyangwe, Chiwoyu, 2014, Post Newspaper accessed online www.postzambia.com, Friday 21 March 2014, 14:40 hours United Kingdom).
The Copperbelt, through its mining and related activities, has produced wealth for
the country, contributing up to 52% (in 1954) to GDP. The mines employ people,
give contracts to local firms, and in the past provided social and economic
infrastructure (ICMM, 2014). However, from the mid-1970s, the sector has
declined considerably with a recent contribution to GDP of 10% only (CSO, 2013).
Research Background
22
While in 1976 the sector had 62,000 employees, between 2008 and 2011, the
sector’s employment stagnated between 30,000 and 53,326 (CSO, 2011). Most of
the mines are employing fewer people because of efficient
mechanisation/automation. Moreover, some of the mines are expected to shut
down after 2017 when some copper deposits are projected to deplete (Mwamba et
al., 2010).
These conditions are particularly compelling to central and local governments,
learning institutions and other stakeholders to define the role of each stakeholder
in efforts to address high unemployment and achieve diversification. Economic
diversification has been a recurrent theme since Zambia’s independence in 1964.
The combination of low copper prices in the 1970s and 1980s and the rising oil
prices created a foreign exchange problem for the country since most of the
machinery, oil, and finished goods had to be imported (Lungu, 2008). This
situation compelled the government to engage in strategies and programmes
aimed at diversifying the economy from copper mining to agriculture,
manufacturing, trading and tourism (Mwamba et al., 2010). Inspite of these efforts,
participation of Zambian citizens in the formal economy is still low and
dependence on Copper has continued; exports data for 2013 shows that non-
traditional exports (NTEs) contributed 24.8% while copper contributed 75.2%
(National Budget, 2014).
Scholars argue that one of the reasons for lack of major success in diversification
has been the absence of a coordinated, sustained and holistic strategy to promote
citizens’ participation in entrepreneurship. Government policies from 1964 hitherto
have not regarded entrepreneurship as a key ingredient to diversification (Lungu et
al., 2007). What was not considered in the several diversification initiatives was a
holistic approach that includes a combination of appropriate institutional
Research Background
23
mechanisms for promoting entrepreneurship and development of entrepreneurial
competencies for Zambians to take advantage of opportunities inherent in the
economy. This would contribute to enhancing diversified formal employment
generation (Lungu et al., 2007).
In a mixed economy, besides growth in foreign direct investment, state-owned
enterprises and existing private-sector businesses, new venture creation also
holds promise in both reducing unemployment and increasing diversification
(Bremmer, 2009; Cook, 2008; Cook, 2010; Fallon et al., 2001; Lungu et al., 2007;
The Economist, 2014; Wennekers and Thurik, 1999). It is hoped that once
potential entrepreneurs are empowered through appropriate training and
institutional support, the resulting enterprises would benefit the economy. The
benefits would include diversified job creation, competitiveness improvement,
more choice for consumers, increase in tax revenue for the government and
wealth for the entrepreneurs themselves (Carree et al., 2002; Criscuolo et al.,
2014; Wennekers and Thurik, 1999; Wennekers et al., 2005).
Research Background
24
2.2.2 Challenges of Unemployment for the Youth
According to the Zambian census report on employment statistics, among the
working age population, 57.4% are economically active and 42.6% are
economically inactive7 (Table 2.2A). Among the economically active individuals,
12.3% are unemployed and 87.7% are employed (Table 2.2B). Furthermore, the
status of those in employment in Table 2.2C indicates that the majority are either
self-employed (44.1%) or unpaid family workers (32.9%). The status of
employment figures further show that 22.3% are employees and the proportion
who are employers is trivial (0.7%), suggesting a need to consider mechanisms to
promote entrepreneurship at a high level.
7 Labour Statistics Terminology (CSO, 2013; ILO, 1993)
Economically active population (labour force) - is the working age population that is available for work irrespective of whether they are employed or not. Economically inactive population- working age population but outside the labour force (e.g. full-
time students, full-time homemakers or housewives and those not available for work for other
reasons such as old age and illness).
Unemployed – persons without work but actively looking for work and/or willing to work.
Employee - a person who works for a public or private employer and receives remuneration in
wages, salaries, commissions, tips, piece rates, or pay in kind.
Self-employed - a person who operates his or her own economic enterprise or engages
independently in a profession or trade, and hires no employees.
An unpaid family worker - a person who works without pay in an economic enterprise operated
by a related family member of the same household (including peasant farmers).
Employer - a person who operates his or her own economic enterprise or engages independently
in a profession or trade, and hires one or more employees.
Research Background
25
Table 2.2 - Unemployment Challenges in Zambia
Source: (CSO, 2013)
The unemployment situation is severe for people under 35 years old. In fact,
77.7% of the unemployed are youth i.e. individuals who are less than 35 years old
(CSO, 2013). The unemployment situation among the youth is so severe that there
Research Background
26
is an urgent need for strategies to increase access to meaningful jobs and career
alternatives. There is a need to design mechanisms to build up the young
generation’s capacity and provide resource access to enable them to start and
manage businesses (Lungu et al., 2007). There is also a need to determine if any
institutional barriers are preventing youth from participating in entrepreneurship
(Agbor et al., 2012). Agbor et al. (2012) in their paper write:
“Africa’s youth population…has been increasing faster than in any other part of the world. 200 million people in Africa fall into this category, making up 20 percent of the population, 40 percent of the workforce, and 60 percent of the unemployed on the continent…Youth in Africa hold great potential as drivers for economic growth through participation in labour markets and also as consumers. A young population can also be a resource that leads to entrepreneurship, innovation and supports governance and political reforms. However, a large youth population that is not gainfully employed can also be a liability (e.g high crime rate), further undermining growth prospects. Africa’s youth present a formidable challenge that requires careful interventions. Deliberations at the 2011 African Union summit noted that high youth unemployment is an impending threat to stability in Africa. Africa must prioritise measures to harness the potential presented by the youth population and to mitigate their risks.” P.9
2.3 Institutional Support for Start-ups and SMEs
To support business start-ups and SMEs, the government over the years has tried
several schemes, but none of them seems to be successful. As indicated earlier,
the post-independence economic history of Zambia has been characterised by the
dominance of copper mining and exports. The performance of the national
economy has thus been closely linked to that of the mining sector. While the
1960s were characterised by high mineral output levels and high world metal
prices, the oil price crisis of the early 1970s adversely affected the copper price.
As a result, before the 1990s under various National Development Plans, one of
the main objectives of the nation was to diversify the economy in order to reduce
the dependence on the copper mining sector. Efforts at diversification included
government’s direct investment in various sectors through establishing state
Research Background
27
owned enterprises. However, these were largely unsuccessful because of failure
to establish robust mechanisms to keep such firms’ operations at arms’ length
from the government and politicians (Lungu et al., 2007).
Furthermore, the diversification efforts also included the government taking the
lead in providing financial services to Micro, Small and Medium-sized Enterprises
(MSMEs). In the early 1980s, for example, the Bank of Zambia (BoZ) set up the
Credit Guarantee Scheme as a means of encouraging private and government
owned commercial banks to extend credit to small-scale industries. Other
important organisations included the Small Industries Development Organisation,
Village Industries Service, and the Small Enterprise Promotion Unit (Mauzu,
2000). Policymakers thought that banks did not extend credit to MSMEs because
of their inability to raise adequate collateral. Thus these schemes relied on
government and donor funds for loans and grants to MSMEs (Maimbo and
Mavrotas, 2003). As a consequence, the schemes and enterprise support
organisations were perceived as social development efforts for ‘helping’ the poor
i.e. clients perceived such schemes as having charitable goals. No wonder
borrowers treated loans from such schemes and the financial sector as if they
were grants that need not be repaid (Mwiya, 2006; Siwale, 2006). Such schemes
also had less emphasis on the need for borrowers or grantees to have business
management and technical skills to ensure survival and success of their fledgling
businesses (Lungu et al., 2007).
With the advent of the third republic in 1991 which ushered in a free market and
liberalised economy, government privatised most of the surviving but largely
unprofitable state owned enterprises. Efforts to diversify the economy and address
high unemployment have included creating an enabling business environment to
attract foreign direct investment. Ironically, foreign direct investment has mainly
Research Background
28
been in the mining sector resulting in continued dependence of the economy on
commodity sales. From the year 2000 onwards, several instruments have been
employed by the government to support the MSMEs sector, including legal
instruments, short and medium term plans (e.g. annual budgets) and policy
statements. For example, since 2006 government has created enterprise support
organisations such as the Zambia Development Agency (ZDA) and the Citizens
Economic Empowerment Commission (CEEC) that administer start-up advisory
services, proffer investment incentives and facilitate access to start-up capital. The
National Technology Business Centre (NTBC) provides incubation services for
innovation and technology based start-ups. In addition, a few non-government
organisations (NGOs) provide support to start-up and fledgling businesses.
Reports from the CEEC, the government organisation that offers start-up debt
finance, indicate that among the nascent entrepreneurs who received support from
2007 to 2011, 58% were not repaying the loans (CEEC, 2012). Research is
required to help stakeholders understand how the current institutional framework
can improve for start-ups and SMEs.
The government now recognises that entrepreneurship skills and support services
are important for entrepreneurship to become a viable career option (National
Vision, 2030; Sixth National Development Plan, 2011-2015; MSMEs Policy 2008-
2018). However, no nation-wide multi-level coordinated efforts exist to offer
training for development of entrepreneurial skills. To generate useful and credible
evidence based recommendations, research is required.
Research Background
29
Ease of Starting and Doing Business in Zambia Table 2.3 shows selected comparative data from the World Bank’s ranking of 189
economies in terms of overall ease of doing business8 and ease of starting a
business9. The World Bank reports indicate that Zambia has recorded
improvements in ease of starting a business over the last five years and its ranking
is generally better than the average ranking of countries in sub-Sahara Africa.
Specifically, for ease of starting a business, there was a significant improvement in
Zambia’s rank from 70 (2013) to 45 (2014). This was mainly due to the elimination
of the minimum paid-in capital requirement at the time of starting up a business. It
was also because the country raised the threshold for Value Added Tax
registration from Zambian Kwacha 200,000 (i.e. US$36,000 per annum) to
Zambian Kwacha 800,000 (i.e. US$150,000 per annum). However, as indicated in
Table 2.3, many challenges for business start-up still remain. Firstly, the number of
procedures required to complete formal registration of a new business (5
procedures) and the number of days (6.5 days) to complete registration of a new
business are still higher than the best performing economy i.e. New Zealand,
where the registration of a business only requires 1 procedure that can be
completed within a half day. Secondly, the cost for registration of a new business
is 26.8% of per capita income compared to the best performing economies i.e.
Slovenia (0%), New Zealand (0.3%) and South Africa (0.3%). Thirdly, a business
8 The World Bank (WB) ranks 189 economies in relation to their ease of doing business, from 1 –
189. A high rank on the ease of doing business index and ease of starting a business means the regulatory environment is more conducive to the starting and operation of a local firm. This index averages the country's percentile rankings on 10 topics, made up of a variety of indicators, giving equal weight to each topic. The 10 topics include: ease of starting a business, dealing with construction permits, getting electricity, registering property, getting credit, protecting investors, paying taxes, trading across borders, enforcing contracts, and resolving insolvency. 9 The ease of starting a business is determined based on: the number of procedures to register a
business, days (time) to complete business registration, cost of business registration as a percentage of per capita income, and required paid-in minimum capital as a percentage of per capita income.
Research Background
30
has to make tax payments 38 times annually, far more than the best performing
economy e.g. 3 times in Hong Kong. Similarly, 183 hours per annum spent on tax
compliance issues for a business is higher than the best performing economy i.e.
United Arab Emirates at 12 hours.
Table 2.3 - Comparative Ease of Starting and Doing Business in Zambia
Source: World Bank’s www.doingbusiness.org, accessed on 19 February 2014 16:00 hours, United Kingdom
Despite recording some improvements in the ease of starting and doing business,
a number of challenges still remain. The World Bank’s new business density index
shows the number of new businesses per 1000 working age adults (15 to 64 year
olds) in a country. In 2010, 2011 and 2012, the index in Zambia was dismal at 1.0,
1.2 and 1.4 respectively (World Bank, 2014). Based on the 2013 data, Zambia’s
new business density is a paltry 1.36 compared to New Zealand’s 15.07, South
Africa’s 6.5 and Botswana’s 12.3. On the other hand, Zambia’s business death
rate is higher at 23.5% compared to the Sub-Saharan Africa average of 16%
(Herrington and Kelley, 2012; Peters, 2014). Therefore, it is necessary to explore
Research Background
31
from the perspectives of would-be entrepreneurs and other stakeholders what
improvements need to be made in the institutional framework to promote
entrepreneurship.
2.3.1 Entrepreneurial Activity in Zambia based on GEM Surveys
Empirically, entrepreneurial activity can be measured differently in terms of relative
share of economic activity accounted for by small firms, data on self-employment,
number of market participants (competition) or indeed firm birth rates relative to
death rates (Kelley et al., 2012; Carree et al., 2002). The GEM reports classify
businesses in any economy into two categories: businesses less than 3.5 years
old are classified as new businesses and those older than 3.5 years are classified
as established businesses. Based on cross-sectional survey data from a sample of
about 2000 individuals in the working age population for each selected country,
the GEM reports the proportion of individuals involved in new business creation,
closing a business and those who own established businesses. For example, in
Table 2.4 below, in 2012, 15% of Zambians reported that they had recently started
a new business, 4% indicated they owned an established business and 20%
reported closing a business recently. The GEM data for 2010 and 2012 show a
decline in the actual new business birth rate from 17% to 15% and a decline in the
proportion of the population that owns and manages an established business from
10% to 4%, respectively. The established business ownership rate at 4% is much
lower than the factor-driven economies average of 11%. To help understand the
reasons for this decline in entrepreneurial activity, there is need to investigate
relevant factors at individual level and in the entrepreneurial environment. This
would enable stakeholders to make informed policy decisions and develop
appropriate interventions (Herrington and Kelley, 2012; Kelley et al., 2011; Kelley
et al., 2012; Martínez et al., 2010).
Research Background
32
Table 2.4 - GEM Comparative Data on Entrepreneurial Activity in Zambia
Compiled from: (Kelley et al., 2011; Kelley et al., 2012)
Clearly, despite an improvement from 24% in 2010 to 20% in 2012, Zambia’s
business death rate (20%) is much higher than the business birth rate (15%). The
net result is a reduction in the number of businesses in the economy. In addition,
the business death rate of 24% in 2010 and 20% in 2012 for Zambia is higher than
the factor-driven economies average of 13% in the same period. This suggests
that a comprehensive detailed study may be necessary to understand the relevant
factors at individual and institutional levels to promote entrepreneurship in Zambia.
2.4 Graduate Unemployment and Graduate Entrepreneurship
This section shows Zambian statistics on graduate unemployment and graduates’
involvement in entrepreneurship.
2.4.1 Graduate Unemployment
The 2010 census data indicates that unemployment in Zambia affects both
university/college graduates and non-graduates alike. In fact, unemployment
Sample Results Reflect % of 18-64
year olds' Responses
2010 2012 2010 2012 2010 2012
Factor-Driven Economies
Zambia (N=2039, N=2157) 17 15 10 4 24 20
Ghana(N=2447,N=2222) 25 23 36 38 26 16
Average(unweighted) 12 13 13 11 13 13
Efficiency-Driven Economies
South Africa (N=3279,N=2928) 4 3 2 2 5 5
China (N=3677,N=3684) 10 7 14 12 6 4
Average(unweighted) 5 6 8 8 4 5
Innovation-Driven Economies
United Kingdom(N=3000,N=2000) 3 4 6 6 2 2
United States(N=4000,N=5542) 3 4 8 9 4 4
Netherlands(N=3502,N=3501) 3 6 9 9 1 2
Average(unweighted) 3 3 7 7 2 3
New
Business
Birth Rate
(≤3.5 yrs)
Established
Business
Ownership Rate
(>3.5yrs)
Business
Death Rate
Research Background
33
among university and college graduates is 20.8% (CSO, 2013). Moreover, 72.3%
of unemployed graduates are below age 35. This means that unemployment is
higher among the youth graduates. Increase in enrolment at tertiary institutions
has led to more graduates entering the labour market than the available job
opportunities; there is an increasing number of educated youth confronted with
rising unemployment. Youth unemployment represents an enormous cost to
society in terms of lost potential for economic growth, negative returns on
investment in education and increase in vices such as crime (Agbor et al., 2012). It
is, therefore, necessary to investigate the determinants of EI in Zambia.
2.4.2 Graduate Entrepreneurship
Graduate entrepreneurship is concerned with the extent to which graduates as
products of university education engage in new venture creation or self-
employment (Nabi and Holden, 2008; Nabi and Liñán, 2011). The 2010 census
data in Zambia on status of employment for graduates indicates that 3.4% are
employers i.e. they operate their own businesses or engage independently in a
profession or trade, and hire one or more employees. In addition, 12.9% are self-
employed i.e. they operate their own businesses or engage independently in a
profession or trade and hire no employees. The rest of the employed graduates
are either employees (82.5%) or unpaid family workers (1.2%). Overall, the census
data indicates that graduates’ involvement in entrepreneurship (employer and self-
employed) is only at 16.3%.
In Zambia, Chimanga (2007) surveyed 38 graduate entrepreneurs and observed
that 57.4% of graduates who own and manage registered businesses are aged
between 22 and 39 years. The majority of these start businesses as a result of
lack of employment opportunities. However, a few graduates quit their jobs in
preference for business start-up to increase their incomes. Additionally, 67.4% of
the graduate entrepreneurs lament that university education prepares them for
Research Background
34
organisational employment rather than starting and managing one’s own business
(Chimanga, 2007). This may suggest that lack of training for starting and
managing one’s own business is a major hindrance to graduate entrepreneurship.
A recent GEM survey on Zambia indicates that 30% of individuals starting
businesses have a secondary education or higher (Herrington and Kelley, 2012).
This means that interest in business by the young and educated seems to be
increasing. Studies conducted in developed countries, such as the USA and the
UK, indicate that individuals who are more educated and more experienced are
more likely to be successfully engaging in entrepreneurship at a high level than the
less educated (Pickernell et al., 2011; Robinson and Sexton, 1994). In the UK,
21% of self-employed individuals hold a university degree (Blanchflower and
Shadforth, 2007). Compared to firms owned and managed by non-graduates,
firms owned and managed by graduates in the UK are more likely to be in
knowledge intensive service industries. Additionally, they are more likely to
experience high growth rates. Furthermore, such firms are more likely to access
external resources such as business advice from informal and formal
networks/trade associations and local authority/government agencies. Lastly, such
firms are also more likely to have public procurement customers (Pickernell et al.,
2011). In a study of EE alumni and a control group for graduates of 9 universities
from 9 European countries, Gibcus et al. (2012) find that EE alumni have
significantly higher positive perception of entrepreneurship, entrepreneurial
knowledge and skills. EE alumni have higher proportions of self-employed
individuals (16% vs 10%) and entrepreneurs (8% vs 3%) than the control group.
Among those who start businesses, the EE alumni start within 0.7 years of
graduation while the control group start after 2.8 years from graduation. In
addition, EE alumni entrepreneurs have higher turnover and innovation in their
Research Background
35
businesses than the control group entrepreneurs. This means that EE helps
graduates to engage in entrepreneurship at a higher level.
Studies on determinants of EI for university students (a proxy for graduates) have
focused on developed countries (Luethje and Franke, 2004; Lüthje and Franke,
2003; Nabi et al., 2010; Solesvik et al., 2013; Souitaris et al., 2007). Scholars
argue that studies carried out in developing countries are required because they
may reach similar or different conclusions from those undertaken in developed
countries. This is possible because there are environmental differences between
developed and developing countries (Bruton et al., 2010; Fayolle and Liñán, 2014;
Hoskisson et al., 2011). For instance, levels of support for business start-ups and
SMEs may be different between developed and developing countries. These and
many other institutional factors may affect graduate entrepreneurship. Since
graduate unemployment is high in Zambia and since graduates are more likely to
engage in entrepreneurship at a higher level, it is worthwhile to target this group in
order to understand which factors affect graduate entrepreneurship.
2.4.3 Entrepreneurship Education in Higher Education in Zambia
A GEM survey in 2010 indicates that past entrepreneurship training is associated
with new business creation. Additionally, developed countries have higher
proportions of individuals who have received entrepreneurship training than
developing countries. No wonder developed countries have higher proportions of
trained individuals involved in business start-up than developing countries (Gibcus
et al., 2012; Martínez et al., 2010). In many developed countries, EE is well
developed and widespread (Consultants, 2008; Kuratko, 2005; Rae et al., 2012;
Solomon, 2007; Solomon et al., 2002; Williamson et al., 2013).
In developing countries such as Zambia, EE is still in its infancy (Brockhaus, 2001;
Kuratko, 2003; Kuratko, 2005; Li et al., 2003; Martínez et al., 2010; Zhou and Cal,
Research Background
36
2010). In Zambia, government policies have begun to recognise that
entrepreneurial skills and entrepreneurship support services are important for
entrepreneurship to become a viable career option (National Vision, 2030; Sixth
National Development Plan, 2011-2015; MSMEs Policy 2008-2018). However, a
holistic approach that includes coordinated and sustained initiatives for
development of entrepreneurial competencies for nascent and potential
entrepreneurs does not exist. Despite an increasing number of universities in
Zambia offering EE since the year 2000, less than 5% of university students
engage in EE. In developed economies like the EU, the EE engagement rates are
higher i.e. between 16% and 23% (Consultants, 2008; Rae et al., 2012). The low
engagement rate in Zambia is perhaps because of lack of empirical evidence on
the impact of EE on EI in Zambia (Fayolle and Liñán, 2014; Küttim et al., 2014). In
Zambia, there is no study to examine how EE is embedded in the curricular.
Neither is there any study on the effect of EE on entrepreneurial intention and
behaviour. Therefore, research is necessary to understand the types of EE that
are offered in the universities and to assess the impact of EE on the society.
2.5 Conclusions
This chapter has discussed the structure of the Zambian economy and its
challenges. Particularly, the chapter highlights the challenge of youth and young
graduate unemployment as well as the need to explore factors that influence
graduate entrepreneurship. Some studies in developed countries indicate that
university graduates, especially EE alumni, are more likely to engage in
entrepreneurship at a higher level. Therefore, investigating determinants of
graduate entrepreneurship would be beneficial to Zambia. Additionally, EE is still
in its infancy in Zambia with little student engagement. Perhaps this is because
there is no clear evidence from Zambia showing the impact of EE on
Research Background
37
entrepreneurship. Therefore, investigating the impact of EE in the Zambian context
would be helpful for policies and practices that aim at promoting entrepreneurship.
The next chapter provides a historical and theoretical overview of
entrepreneurship and its determinants.
38
CHAPTER 3: ENTREPRENEURSHIP – HISTORICAL AND THEORETICAL
OVERVIEW
3.0 Introduction
As a background to the current research, the preceding chapter discusses the
Zambian economy’s structure, the challenge of youth and graduate unemployment
and the status of entrepreneurship education (EE) in universities. The current
chapter aims to develop a historical and theoretical overview of entrepreneurship.
The chapter has four major sections: the classical approach highlights the role of
entrepreneurship in an economy (3.1); the psychological approach indicates the
typical psychological attributes of entrepreneurs (3.2); the sociological approach
focusses on socio-cultural factors that shape entrepreneurial behaviour (3.3); and
lastly, the processual approach highlights the steps and actions involved in
exploiting entrepreneurial opportunities (3.4).
3.1 The Classical Approach
The earliest references to entrepreneurship emanate from the field of economics
on the nature and sources of profit. Initially, all economic value is thought to
originate from a combination of three factors of production; land, labour and capital
(Smith, 1776). In this regard, entrepreneurship refers to all activities that create
residual profits in excess of the rate of return on the three factors of production
(Matlay, 2005). The classical views indicate that entrepreneurship is about
organising production/service while bearing uncertainty and taking risk through
commercial activity.
3.1.1 Classical Views of the Entrepreneur
The term ‘entrepreneur’ originates from the French word ‘entreprendre’. It means
‘undertake’ or ‘go-between’ (Cantillon, 1755). The entrepreneur is one who
Historical and Theoretical Overview
39
undertakes actions to organise and manage a business. The classical views
describe the entrepreneur as a project manager, an organiser of resources and a
manager of uncertainty and risk (Osborne, 1995; Gartner, 1989b).
3.1.1.1 Entrepreneur as Project Manager
The meaning of entrepreneurship has evolved over the centuries. The initial
recorded conceptualisation takes Marco Polo (1254 AD -1324 AD) as an example
in explaining the role of entrepreneurship in the market (Hisrich et al., 2005).
Marco Polo was a citizen of the Venetian Republic; the republic lasted from 697AD
to 1797 AD in northern part of present Italy. He established trade routes to Asia
based on demand from consumers who were separated by geography and culture.
He signed contracts with venture capitalists for funds to enable him to purchase,
transport and sell goods. While both Marco Polo (the merchant-adventurer) and
the venture capitalists were financial and market risk takers, Marco Polo also took
on operational, physical and emotional risks. Upon completion of the trip, the
profits were used to repay the venture capitalist and the residual belonged to the
adventurer (Osborne, 1995). Besides Marco Polo’s example, an entrepreneur was
also perceived as an individual managing construction or production projects
usually funded by the government (Hisrich et al., 2005; Osborne, 1995). In this
case, the entrepreneur’s role was managerial in nature since he/she neither
owned nor financed the enterprise (Hisrich et al., 2005).
3.1.1.2 Entrepreneur as Organiser of Resources
In scholarly literature, the word ‘entreprendre’ and the role of the entrepreneur first
surfaced in the writings of Richard Cantillon, an Irish economist living in Paris
(Cantillon, 1755). Cantillon makes pioneering theoretical contribution to the fields
of economics and entrepreneurship (Cantillon, 1755; Cantillon, 2010; Hébert,
Historical and Theoretical Overview
40
1981). Broadly, Cantillon deals with a wide variety of fundamental and
philosophical issues such as production, distribution and consumption of goods
and services; money and interest; international trade and business cycles; and
the role of government in the economy (Herbert, 1981). Specific to
entrepreneurship, his writings argue that the best way to produce consumer goods
for any economy is to allow free markets where entrepreneurs could be counted
on to make self-interested judgments on what would best please their consumers
(Smith, 1776). Cantillon’s views demonstrate that entrepreneurial self-interest will
regulate any economy better than if government decides to make all economic
decisions on behalf of its citizens (Cantillon, 2010).
Cantillon viewed the entrepreneur as a critical figure in the economy, an organiser
of production factors, and a prime director of resources, taking chances and facing
uncertainty in the process. Entrepreneurship is associated with all activities that
create residual profits in excess of the rate of return for land, labour and capital
(Mises, 1949; Ripsas, 1998). In his Essai Sur la Nature du Commerce en General
(Essay on the Nature of Trade in General), Cantillon conceptualises
entrepreneurship as self-employment of any and every sort. As long as the person
is not hired or working for wages, but is engaging in commerce on his/her own,
then he/she is an entrepreneur (Cantillon, 2010). Entrepreneurs’ occupations
come with uncertainty emanating from either the competition or changing tastes of
customers. Thus, the entrepreneur’s profits are always uncertain; they could be
very large but there is also the prospect of bankruptcy.
Cantillon categorises and conceptualises the roles of the economically active
population into property owners who receive rental income; capitalists who receive
interest income; employees (those hired) who receive wages; and entrepreneurs
Historical and Theoretical Overview
41
who take the risks of organising and managing the factors of production for goods
and services that the population needs. Cantillon also identifies two types of
entrepreneurs. Firstly there is one group that requires capital for their commercial
activities (e.g. traders and manufacturers). These buy at ‘certain price and sell at
an uncertain price’. Secondly, there are entrepreneurs who provide a service to
the market based on their professional/technical skills (e.g. painters, physicians,
lawyers); these entrepreneurs do not require capital but only need their skills in
order to engage in commerce (Gibcus et al., 2012). Both types of entrepreneurs
have to deal with uncertainty as they manage their businesses. Here Cantillon
introduces, for the first time, the theory of entrepreneurship. Cantillon's writings are
regarded as the first systematic work over the whole field of entrepreneurship, let
alone economics (Schumpeter and Backhaus, 1934; Schumpeter, 1954).
3.1.1.3 Entrepreneur as Manager of Risk and Uncertainty
Turgot distinguishes the entrepreneur from the capitalist by arguing that the former
is one who combines factors of production in new ways while the latter provides
the requisite funds (Turgot, 1766). Contrary to Cantillon’s view, Turgot argues that
it is the capitalist who faces the ultimate uncertainty. Jean Baptiste Say (1821)
separates the profits of the entrepreneur from the profits of capital. Using an
example of a family business, he observes that the owner could receive profit as
the entrepreneur, salary as a manager, and interest as the investor of capital. Say
further argues that the entrepreneur not only undertakes the role of
"superintendence and administration" but also exhibits the attributes of judgement,
perseverance, knowledge of the world of business, and ability to organise
production (Say and Richter, 1816; Say, 1821). Scholars indicate that Say
deviates from classical economists in his concept of the entrepreneur; classical
economists, like Adam Smith, consider the entrepreneur to be part of the market
Historical and Theoretical Overview
42
forces (‘the invisible hand’) and, therefore, do not attempt to recognise his/her
specific role in the economy (Kirchhoff, 1994). Say, like Turgot, views the
entrepreneur as someone who organises and coordinates production activities; he
suggests that entrepreneurship is the fourth factor of production, the other factors
of production being land, labour and capital.
John Stewart Mill is often credited with bringing the term ‘entrepreneurship’ into
main stream economics literature in the English language (Mill, 1848). He
identifies direction, control, superintendence and risk bearing as the prime
functions of the entrepreneur. However, Mill does not attempt to differentiate the
role of the entrepreneur from that of the capitalist. Hawley (1907) suggests that the
rewards of enterprise accrue to the owner due to the assumption of uncertainty
and responsibility. The risk theory of profit clearly asserts that managers can
create profits due to incremental innovation but unless they also take risk of
ownership, they are not entrepreneurs (Hawley, 1907; Knight, 1921).
In America, Knight (1921) identifies the restrictions within which economic theory
is formalised and attempts to place entrepreneurship and the firm outside those
restrictions. He does so by distinguishing between risk and uncertainty. He
expands Cantillon's concept of uncertainty by suggesting that the entrepreneurs
bear the responsibility and consequences of making decisions under uncertainty
and risk. Indeed before a new product or service is introduced, a person cannot
know with certainty that he or she can produce desired outputs (technical risk),
meet consumers’ needs (market risk), generate profits in the face of competition
(competitive risk), and be able to repay debt and meet the financial expectations of
shareholders (financial risk). Knight further emphasises the key distinction
between insurable risk and non-insurable uncertainty (Knight, 1921; Shane, 2003;
Historical and Theoretical Overview
43
Wu, 1989). For Knight, risk implies knowledge of the probability that an event will
occur and this is insurable. Uncertainty is immeasurable and, therefore, not
insurable. He stresses that because of the unique uncertainty of entrepreneurship,
it cannot be insured, capitalised or salaried (Knight, 1921). In this regard, he
argues that decisions under uncertainty extend beyond the evidence and depend
on the individual. Knight’s entrepreneur is a manager of uncertainty. From a macro
perspective, Cantillon, Say and Knight see entrepreneurship as a way of
managing resources, risk and uncertainty to meet market needs and improve the
efficiency of an economy (Acs, 2006; Brockhaus Sr, 1980; Mescon and Montanari,
1981; Reynolds et al., 1999).
The foregoing classical views depict the entrepreneur as an organiser and a
manager under conditions of risk and uncertainty. The ability to accommodate the
unexpected and overcome problems is a key attribute of entrepreneurship.
However, these writers place the entrepreneur in a particularly stable environment
and not in a dynamic environment. In addition, the writers do not include the
innovative role of the entrepreneur. These are perspectives addressed by neo-
classical theorists.
3.1.2 Neo-Classical Views
The neo-classical views of the entrepreneur became prominent around 1879. They
focus on aggregate equilibrium results in an economy rather than adjustment
processes at a micro level that Cantillon and Say address. Under this broad term,
these economists pursue and expound macroeconomic analyses of the `balance'
between aggregate supply and aggregate demand (Guzman-Cuevas, 1994). The
neo-classical views combine the functions of the capitalist and the entrepreneur.
The entrepreneur is seen as an abstract figure, unconcerned about the influences
external to the rational operation of the firm he/she directs (Greenfield and
Historical and Theoretical Overview
44
Strickon, 1981; Greenfield and Strickon, 1986). Scholars argue that the absence of
a specific mechanism for creation of new demand is the greatest weakness of
neo-classical economic theories (Greenfield and Strickon 1981, 1986).The specific
role of the entrepreneur did not become prominent in the writings of neo-classical
economists until they turned their attention to problems associated with economic
growth. In this regard, some neo-classical economists expound on how micro-level
decisions and actions of the entrepreneur influence economic activity.
A few neo-classical economists make notable contributions to entrepreneurship.
For Walras, the entrepreneur mainly performs an administrative function by
coordinating production activities and capital. This view combines the role of the
entrepreneur and the capitalist (Walras and Jaffé, 1898). For Keynes, the
entrepreneur is the decision maker within a firm responsible for investment
decisions and bearing uncertainty in his or her predictions of forecast demand
(Keynes, 1936). Furthermore, Marshall, in his "Principles of Economics" book,
emphasises the distinguishing nature of the entrepreneur's organisational and
leadership role from that of a conventional manager (Marshall, 1920). The
prominent views of Kirzner and Schumpeter on the role of the entrepreneur are
discussed next.
3.1.2.1 Kirznerian Entrepreneurship
Kirznerian entrepreneurship entails taking advantage of opportunities through
discovery of profitable discrepancies, gaps, and mismatches in knowledge and
information that others have not yet perceived or exploited. Typically, the
entrepreneur is alerted to a new product, a superior production process, or a price
mismatch (arbitrage) and acts to capitalise on the opportunity which that discovery
presents (Hayek, 1945). These activities increase knowledge about the situation,
Historical and Theoretical Overview
45
reduce the general level of uncertainty over time, and promote market processes
that help to reduce or eliminate the gap between market leaders and followers.
In relation to the nature of entrepreneurship, main stream Austrian economists
argue that the entrepreneur profits from his/her alertness to opportunities that exist
in an uncertain, non-equilibrium situation (Mises, 1949). This alertness enables the
entrepreneur to perceive and act on those opportunities before others do (Kirzner,
1973; Kirzner, 1978; Kirzner, 1997). Kirzner, Mises and Hayek’s argument is that
markets are constantly in states of disequilibrium and alertness to disequilibrium is
the key characteristic of the entrepreneur. They emphasise that entrepreneurship
does not create disequilibrium but rather it has an equilibrating role. This is the role
that entails actions necessary to shift markets towards a state of equilibrium by
identifying gaps in the market (entrepreneurial opportunities) and filling those
gaps. The entrepreneur is alert to opportunities that exist, rather than, as
explained by Schumpeter, creating new opportunities.
Schultz’s Human Capital Approach to Adjustments to Disequilibria Contributing to Kirzner’s perspectives, Schultz suggests that markets do not
automatically and instantaneously regain equilibrium following an exogenous
shock. The continual emergence of opportunities is central to entrepreneurship.
The source of opportunities is disequilibria that are inevitable in the dynamics of
modernisation and economic growth (Schultz 1982, p.439). There are many
sources of these disequilibria (and, hence, opportunities) and they include those
arising from technical progress (innovation) and demographic shifts in population.
“Regaining equilibrium takes time, and how people proceed over time depends on
their efficiency in responding to any given disequilibrium and on the costs and
returns of the sequence of adjustments available to them” (Schultz 1975, p. 829).
He takes innovation as given, and focuses on how economic agents adjust to
Historical and Theoretical Overview
46
exogenous shocks. In Schultz’s formulation, entrepreneurship is the ability to
adjust, or reallocate resources, in response to changing circumstances (Schultz,
1975; Schultz, 1979; Schultz and Schultz, 1982; Schultz, 1982). The ability to
identify, develop and exploit new opportunities can be enhanced through
investment in skills and knowledge (Cook, 2008). Like any other forms of human
capital, entrepreneurial ability (i.e. the ability to deal with disequilibria) can be
enhanced through education, training and experience (Holmes and Schmitz Jr,
1990; Klein and Cook, 2006; Schultz and Schultz, 1982). This perspective is
consistent with human capital theory which posits that relevant skills, knowledge
and experience can lead to higher performance outcomes (Becker, 1962; Becker,
2009; Ployhart and Moliterno, 2011; Unger et al., 2011).
3.1.2.2 Schumpeterian Entrepreneurship
Schumpeter (1934) perceives the entrepreneur as a person who conceives and
executes “new combinations” of factors in production and, thus, plays a key role in
market and economic development processes. Schumpeter is regarded as the
father of entrepreneurship and innovation because of his contribution to the
entrepreneurship theory (Gedeon, 2010; Hock-Beng, 1990). Schumpeter suggests
two theories of entrepreneurship (Hock-Beng,1990). Firstly, he proposes that
innovation and technological change of a nation comes from entrepreneurs, or
“wild spirits”. He uses the word ‘Unternehmen or Unternehmergeist’, German for
entrepreneur-spirit. It is literally translated from the French word “entreprendre"
which means 'take in hand' or 'undertake' some activity. Schumpeter indicates that
entrepreneurs are the ones who make things work/happen in any economy. He
further suggests that some degree of monopoly power is necessary to encourage
entrepreneurs to continue innovating.
Historical and Theoretical Overview
47
Secondly, Schumpeter predicts that because large organisations are more likely to
have capacity to invest in research and development, they would produce most of
the innovations. Accordingly, large monopolistic enterprises would be the principal
engines of technological progress as they are likely to have the necessary
resources to undertake complex technological activities. These large firms are also
threatened by “creative destruction” (the continuous process of superior
innovations displacing inferior technologies). To operationalise his theses,
Schumpeter proposes that economic change revolves around innovation,
entrepreneurial activities and market power. He argues that innovation-originated
market power could provide better economic results than the invisible hand and
price competition. Additionally, technological innovation often creates temporary
monopolies, allowing abnormal profits that would soon be reduced by new
entrants who are rivals and imitators. These temporary monopolies are necessary
to create the incentive necessary for firms to develop new products and
processes. Furthermore, Schumpeter differentiates inventions from innovations
arguing that as long as inventions are not carried into practice, inventions are
economically irrelevant. Therefore, the role of entrepreneurs is to turn inventions
into innovations (Hock-Beng, 1990).
“…the function of entrepreneurs is to reform or revolutionise the pattern of production by exploiting an invention or, more generally, an untried technological possibility for producing a new commodity or producing an old one in a new way, by opening up a new source of supply of materials or a new outlet for products, or by reorganising an industry and so on… This kind of activity is primarily responsible for the recurrent “prosperities” that revolutionise the economic organism and the recurrent “recessions” that are due to the dis-equilibrating impact of the new products or methods. To undertake new things is difficult and constitutes a distinct economic function, first, because they lie outside of the routine tasks which resist in many ways… from simple refusal either to finance or to buy a new thing, to physical attack on the man who tries to produce it”. Schumpeter, 1950 (quoted from Hock-Beng, 1990, p.342)
Historical and Theoretical Overview
48
The key attributes and aptitudes evident from Schumpeter’s entrepreneur are
innovativeness, self-confidence, daring, creativity, and desire to break routines.
Schumpeter's "creative destruction" implies that entrepreneurs create new wealth
through the process of destroying existing market structures (thus, causing market
disequilibrium) as their innovations increase new demand and create new wealth.
This view is contrary to Kirzner’s view that depicts the market as largely static, the
only changes being adjustments from one competitive market equilibrium to
another. “Schumpeter’s entrepreneur acts to disturb an existing equilibrium
situation. By contrast, my own treatment of the entrepreneur emphasises the
equilibrating aspects of his role” (Kirzner, 1973, p72-73). Schumpeter's theory
argues that the market is dynamic and depends on continuous change in buyer
and supplier behaviour. Schumpeter’s entrepreneurs are change agents and their
activities result in innovations, systemic changes, and new market development
processes (Kirchhoff, 1994; Hong-Beng, 1990).
In summary, the economic approach (also known as classical and neo classical
approach) to entrepreneurship focuses on the role of the entrepreneur in the
economy in market development (Cope, 2005). This approach depicts the role of
the entrepreneur in the market (leading to equilibrium) when consumers’
preferences are predicted correctly and profitable market gaps are spotted and
filled. The exception is Schumpeter who sees the entrepreneur as engaging in
innovation or creative destruction (leading to market disequilibrium). The overall
critique against this approach is that it ignores the institutions (environment) that
impact on entrepreneurs’ behaviour (Shane, 2003; Schultz, 1982; Cope, 2005).
Historical and Theoretical Overview
49
3.2 Psychological Approach
This approach suggests that some individuals have certain psychological
characteristics that determine whether or not one finds the tasks and roles of
entrepreneurship attractive and viable (McClelland, 1965). Given the same
information and skills, individuals with characteristics relevant to entrepreneurship
are more likely to pursue an entrepreneurial opportunity (Shane, 2003). Scholars
indicate that relevant traits are one of the critical determinants of the new venture
creation decision. In fact, empirical studies indicate that relevant traits are
particularly critical at the intention stage. However, their significance reduces at
nascence and growth stages when skills and knowledge become more important
(Frank et al., 2007). The beginning of the psychological approach can be traced to
Smiles (1859). In describing the famous Victorian entrepreneurs, he identifies the
entrepreneur by key psychological characteristics (Smiles, 1859). These
characteristics include integrity, self-learning, courage, conscientiousness,
patience, perseverance, self-discipline and self-respect. In explaining the
innovation or ‘creative destruction’ process of entrepreneurship, Schumpeter
(1950) describes the persons that are more likely to exploit entrepreneurial
opportunities as extraordinary and few:
“…to act with confidence beyond the range of familiar beacons and to overcome the resistance, requires aptitudes that are present in only a small fraction of the population and that define the entrepreneurial type as well as the entrepreneurial function…Schumpeter, 1950.” (quoted in Hock-
Beng,1990, p.342)
From the late 1960s until the 1980s, the emphasis on individual characteristics of
entrepreneurs became known as the traits school of entrepreneurship (Low and
MacMillan, 1988; Shaver and Scott, 1991; Solomon and Winslow, 1988). Some
scholars indicate that while some characteristics can be developed through
training and experience, other characteristics are innate (Gibb, 2007; Klein and
Historical and Theoretical Overview
50
Bullock, 2006; Shuman et al., 1985; Timmons et al., 1987). In the psychology
literature, following the work of Costa and McCrae (Costa Jr and McCrae, 1992;
McCrae and Costa, 1985; McCrae and Costa Jr, 1989; McCrae and Costa, 2004),
personality traits are grouped into five dimensions constituting the big-five factor
model. The five factors are extraversion (extroversion or introversion), openness to
experience, neuroticism (emotional instability), conscientiousness and
agreeableness. Meta-analyses of empirical studies indicate that people who score
highly on extraversion, openness to experience and conscientiousness, and low
on neuroticism and agreeableness are more likely to be entrepreneurs (Hermann,
2011; Zhao et al., 2010a). Openness to experience is akin to innovativeness and
risk taking; conscientiousness is related to need for achievement.
The broad range of psychological factors identified in the literature can be
organised into a few categories: personality and motives, core self-evaluation
characteristics, cognitive characteristics and other attributes (Table 3.1).
Table 3.15- Classification of Entrepreneurial Characteristics CHARACTERISTICS LITERATURE
A. Personality and Motives
Need for achievement/ conscientiousness
(McClelland, 1961; Volery et al., 2013; Zhao et al., 2010a)
Risk taking propensity/ openness to experience
(Brockhaus Sr, 1980; Frank et al., 2007; Knight, 1921)
Desire for freedom/independence (Burke et al., 2000; Caird, 1991; Meredith et al., 1982)
Disagreeableness/deviancy (Barrick and Mount, 1991; Brodsky, 1993; De Vries, 1977; Deakins et al., 1996)
Extraversion (Barrick and Mount, 1991; Bhide, 2000; Zhao and Seibert, 2006; Zhao et al., 2010a)
B. Core Self-evaluation
Internal locus of control/emotional stability/proactivity
(Bonnett and Furnham, 1991; Rauch and Frese, 2007; Rotter, 1966; Shapero, 1975)
Generalised self-efficacy (Ainuddin et al., 2006; Bandura, 1977; Chen et al., 1998; Rauch and Frese, 2007)
C. Cognitive Characteristics
Over-confidence (Arabsheibani et al., 2000; Busenitz and Barney, 1997)
Representativeness Busenitz and Barney (1997)
Intuitiveness (Allinson et al., 2000; Busenitz and Barney, 1997)
Historical and Theoretical Overview
51
In Table 3.1, the first two categories (A and B) comprise fundamental
characteristics of a person that endure over time and acount for consistent
patterns of responses to everyday situations (Rauch and Frese, 2007). People can
and do change their personalities, motivations and core self-evaluation but these
changes are rare and relatively difficult to achieve. In contrast, cognitive
characteristics (the way people think or process information and make decisions)
tend to vary significantly over time and are situation dependent (Shane, 2003).
These psychological factors will influence the decision to engage in
entrepreneurship.
3.2.1 Personality and Motives
Personality and motives are fundamental characteristics of individuals and lead
them to behave a certain way consistently. Faced with the same information, skills,
opportunity or cost, some people will decide to exploit an opportunity while others
will not. The major personality and motivation attributes associated with
entrepreneurship are: risk taking propensity, need for achievement, desire for
independence, extraversion and agreeableness (Rauch and Frese, 2007; Shane,
2003; Zhao and Seibert, 2006; Zhao et al., 2010a).
Risk Taking Propensity
This is an aspect of personality that refers to a person’s willingness and readiness
to engage in risky activity. People with higher risk-taking propensity (RTP) are
more likely to choose to exploit opportunities because such individuals feel
capable of thriving in the uncertainties associated with entrepreneurship (Knight,
1921; Wu, 1989). In addition, individuals with high RTP are eager to engage in
activities or situations that involve unceratinty and, therefore, they would find
entrepreneurship to be attractive and possible (Franke and Luethje, 2003). Most
empirical studies find that, with a few exceptions such as Marques et al. (2012),
Historical and Theoretical Overview
52
individuals with higher RTP are more likely to become entrepreneurs (Sánchez,
2013; Stewart Jr and Roth, 2001; Zhao et al., 2005).
Need for Achievement
Need for achievement (NAch) is an individual’s persistence, hard work and
motivation for significant accomplishment (McClelland, 1961; McClelland, 1965;
McClelland, 1967). For McClelland, a high NAch is a motivation that leads people
to undertake activities and tasks that demand individual effort and skill, and
provide clear feedback on outcomes. Except for a few studies that indicate
otherwise (Cromie, 2000; Littunen, 2000), most empirical research finds support
for the proposition that individuals who have a higher NAch are more likely to be
entrepreneurs (Collins et al., 2004a; Dohse and Walter, 2012; Frank et al., 2007;
Kristiansen and Indarti, 2004; Rauch and Frese, 2007; Volery et al., 2013). This is
because NAch drives individuals to seek careers and tasks in which performance
is due to one’s own efforts and not the efforts of others. Therefore, individuals with
high NAch are more likely to find entrepreneurship attractive (McClelland, 1965).
Desire for Independence
This is an aspect of personality in which an individual prefers to engage in
independent action as opposed to action involving others or under the
supervision/control of others (Wu, 1989). Empirical studies find that the desire to
do things one’s way and to be in control is a common reason given by firm
founders (Caird, 1991; Cromie, 1987; Kolvereid, 1996b).
Extraversion
This is an aspect of personality that incorporates the attributes of sociability,
assertiveness, activeness, ambition, initiative, expressiveness, gregariousness,
exhibitionism, talkativeness, urgency and impetuousness (Barrick and Mount,
Historical and Theoretical Overview
53
1991; Zhao et al., 2010a). People with this characteristic are more likely to choose
to engage in entrepreneurship. This is because entrepreneurs identify
opportunities that are not apparent to others; they often have to deal with the
challenge of persuading others like customers, employees and investors that the
opportunity they have seen is valuable and viable. Empirical studies and meta-
analyses thereof find support for these propositions (Babb and Babb, 1992; Burke
et al., 2000; Hermann, 2011; Wooten et al., 1999).
Agreeableness
This characteristic incorporates friendliness, social conformity, compliance,
flexibility, tendency to trust, cooperativeness, tendency to forgive, tolerance,
softheartedness, and courteousness (Barrick and Mount, 1991). People with this
characteristic are less likely to be entrepreneurs. An entrepreneur must have a
critical approach to information enhanced by a suspicious non-trusting and
sceptical nature. This is necessary for one to consider different perspectives on an
issue during decision-making. Empirical studies and meta-analyses thereof find
support for the notion that entrepreneurs tend to be less agreeable and less
trusting (i.e. more suspicious) than non-entrepreneurs (Brodsky, 1993; Fraboni
and Saltstone, 1990; Zhao and Seibert, 2006).
3.2.2 Core Self–Evaluation Characteristics
Core self-evaluation is a psychological concept that is related to locus of control,
generalised self-efficacy, self-esteem and neuroticism (Shane, 2003). Judge et al.
(2002) argues that the characteristics of locus of control, generalised self-efficacy,
self-esteem and neuroticism focus on a person’s sense of control over his or her
own affairs i.e. one’s general belief that he or she can influence any outcomes
through effort and capability. Studies in psychology indicate that these
Historical and Theoretical Overview
54
characteristics deal with the same higher order concept and, therefore, are related.
People with high levels of internal locus of control will have high self-esteem, high
generalised self-efficacy and emotional stability (Judge et al., 2002).
Internal Locus of Control
Internal locus of control (ILC) is a person’s belief that he/she can determine his/her
own success through effort and capability, not the environment (Rotter, 1966). An
individual with high ILC underplays the influence of luck, fate and external
obstacles in goal attainment. On the other hand, an individual with low ILC
believes that factors beyond one’s control determine outcomes (Rotter, 1966).
With a few exceptions (Altinay et al., 2012; Chell et al., 1991), most empirical
evidences in prior studies indicate that individuals with high ILC are more likely to
start a business (Lee and Tsang, 2001; Lüthje and Franke, 2003; Rauch and
Frese, 2007). The rationale is that the belief that an individual forms about the
value of entrepreneurial opportunities depends partly on self-evaluation of one’s
own abilities to exploit those opportunities (Rauch and Frese, 2007; Frank et al,
2007). This self-evaluation depends on the degree to which the individual believes
he or she can influence the outcomes. Individuals with high ILC believe they can
influence any outcomes. Therefore, they are more likely to consider
entrepreneurship to be possible and worthwhile.
Generalised Self-efficacy
Generalised self-efficacy (GSE) reflects a general tendency to view oneself as
capable or incapable of meeting task demands in a wide variety of contexts
(Bandura, 2001). Individuals with high GSE are more likely to exhibit personal
initiative, search for achievable but challenging opportunities, and persevere when
encountering any challenges (Casson, 1995; Chen et al., 2004; Ripsas, 1998; Wu,
1989). No wonder empirical evidence indicates that such individuals are more
Historical and Theoretical Overview
55
likely to consider business start-up attractive and possible (Ainuddin et al., 2006;
Chen et al., 1998; Markman et al., 2002; Robinson et al., 1991).
3.2.3 Cognitive Characteristics
Cognitive characteristics are factors that influence how people think and make
decisions (Busenitz and Barney, 1997). Compared to personality, motives and
core self-evaluation characteristics, cognitive characteristics tend to change
overtime. They tend to be more heavily influenced by a person’s perception of the
situation he/she is involved in. To exploit an entrepreneurial opportunity, a person
must make decisions under uncertainty and perhaps with limited information.
These are conditions that allow subjective approaches or rules of thumb in
decision making i.e. making decisions by exploring possibilities rather than
following objective rules (Busenitz and Barney, 1997; Casson, 1995; Wu, 1989).
“Biases and heuristics are decision rules, cognitive mechanisms, and
subjective opinions people use to assist in making decisions in situations of uncertainty and limited information. Frequently, the use of biases and heuristics yields acceptable solutions to problems for individuals in an effective and efficient manner…"biases and heuristics" is used to refer to… simplifying strategies that individuals use to make decisions, especially in uncertain and complex conditions.” Busenitz and Barney (1997, p.12)
In situations involving uncertainty and incomplete information, such as evaluation
and exploitation of entrepreneurial opportunities, more comprehensive and
cautious decision-making is not possible, and rules of thumb may provide an
effective way to approximate the appropriate decisions. The use of heuristics has
also been found to be associated with innovativeness. Practically, without
employing subjective approaches, many entrepreneurial decisions would never be
made. With entrepreneurial ventures in particular, the opportunity would often
disappear by the time all necessary information becomes available for rational
decision-making. The cognitive characteristics associated with entrepreneurship
include:
Historical and Theoretical Overview
56
a) Overconfidence i.e. optimism bias which is reflected in the tendency to
overestimate the probability of being right in the face of uncertainty and
incomplete information (Busenitz, 1999). Empirical evidence indicates that
overconfident individuals are more likely to start a business (Arabsheibani
et al., 2000; Bhide, 2000; Busenitz and Barney, 1997; Gartner and Thomas,
1989; Gartner and Thomas, 1993);
b) Representativeness i.e. making generalisations and decisions from a small
sample or incomplete information (Busenitz and Barney, 1997). Empirical
evidence indicates that entrepreneurs, compared to managers, are more
likely to use rules of thumb in decision making rather than undertaking
extensive statistical analyses (Busenitz and Barney, 1997; Katz, 1992;
Porter, 1980); and
c) Intuition i.e. a feeling that something is true without gathering information
(Baumol, 1993). Empirical evidence indicates that entrepreneurs have a
tendency to rely on intuition in the absence of complete information
(Allinson et al., 2000; Baron, 2000).
3.2.4 Overall Critique of Psychological Trait Approach
Some scholars criticise research which attempts to develop personality profiles of
the entrepreneur. Such critics encourage research on behaviours and activities of
entrepreneurs, rather than psychological traits (Jenks, 1950; Kilby, 1971). There
are many reasons for these critiques. Firstly, it is not clear whether entrepreneurs
possess these attributes from birth or acquire them as a result of: a) being
entrepreneurs (Chell et al., 1991; Chell, 2000; Krueger and Dickson, 1994); b)
being in a cultural setting that favours entrepreneurship (Kristiansen and Indarti,
2004; Shinnar et al., 2012); or c) grasping entrepreneurship knowledge and skills
(Hansemark, 1998; Rasheed, 2000; Rasheed and Rasheed, 2003).
Historical and Theoretical Overview
57
Secondly, prior empirical studies report mixed conclusions. Characteristics such
as risk taking propensity, locus of control and tolerance for ambiguity sometimes:
a) lower the business start-up intention (Solesvik et al., 2013); and b) have no
significant effect on start-up intention (Altinay et al., 2012). Chell (2000) argues
that very few entrepreneurs possess all of the attributes or if they do they combine
them differently. Some empirical studies (Brockhaus Sr, 1980; Brockhaus and
Nord, 1979; Ertuna and Gurel, 2011; Fairlie and Holleran, 2011; Gurel et al., 2010;
Hansemark, 2003; Sexton and Kent, 1981) find that when certain psychological
traits are carefully evaluated, it is not possible to consistently distinguish
entrepreneurs from non-entrepreneurs (Gartner, 1989a; Gartner, 1989b).
Thirdly, scholars increasingly advocate for theoretical models that reflect that an
individual’s behaviour may be determined by interactions between individual
factors and environmental factors (Faulconer and Williams, 1985; Gergen, 1985;
Hitt et al., 2007; House et al., 1996; Shepherd, 2011). Consequently, some
scholars suggest that inconsistent findings may be addressed by cross level
studies that simultaneously take into account the influence of contextual factors
(Frank et al., 2007; Gartner, 1989a; House et al., 1996; Shepherd, 2011).
3.3 Sociological Approach
The sociological approach to entrepreneurship is based on social behaviour
theories. It emphasises the environmental or situational determinants of
entrepreneurial behaviour; it focuses on the person in context (Atkinson et al.,
1983; Bandura, 1982; Bandura, 1977; Chen et al., 1998; Mauer et al., 2009;
Mueller and Thomas, 2001; Shapero, 1975; Shapero, 1981; Shapero and Sokol,
1982). Bandura (1977) distinguishes social learning theory (SLT) from traditional
psychological theories by emphasising reciprocal influence among cognition,
Historical and Theoretical Overview
58
behaviour and environment. Whereas traditional unidirectional theories depict
human behaviour as caused either by environmental factors or internal
dispositions, SLT explains human behaviour in terms of triadic reciprocal
influences (Figure 3.1). This means that an individual’s behaviour (B) is affected
by interactions amongst cognitive and other individual factors (C) and the
environment (E).
Source: (Chen et al., 1998) Figure 3.1- Behaviour (B), Cognition (C) and Environment (E) Interaction
Atkinson et al. (1983, p.58) suggest that ‘‘to predict behaviour, we need to know
how the characteristics of the individual interact with the characteristics of the
environment.'’ Furthermore, SLT indicates that individual differences in behaviour
emanate largely from differences in the types of learning experiences encountered
in the course of growing up and/or socialisation (Bandura and Albert, 1989). These
experiences may affect one’s perceived self-efficacy toward certain tasks. Self-
efficacy is the extent to which an individual believes in his or her capability to
undertake a particular task in a given environment (Mauer et al., 2009). Based on
SLT, behavioural patterns are learnt through: a) mastery experiences (prior
actual, related or simulated experience of something and the associated
positive/negative feedback); b) role modelling and vicarious experiences i.e.
observation of credible role models of the behaviour and the consequences of the
behaviour; and, c) social persuasion i.e. what is acceptable is learnt through social
Historical and Theoretical Overview
59
peer pressure and social discourse (Krueger and Dickson, 1994; Scherer et al.,
1989).
Chell et al. (2001) argue that individuals develop expectancies and values from
social experiences. These social experiences in turn influence the person's
perception of the entrepreneurial role and its value (Chell, 1985; Chell et al., 1991;
Chell, 2001). Therefore, individuals’ perceived entrepreneurial capability and the
consequent behaviour can be understood in terms of the types of situations
encountered and the social (reference) groups to which individuals relate
throughout their lives (Gibb and Ritchie, 1982). Specifically, family background,
situational factors and the wider environment of entrepreneurship are sources of
influence.
3.3.1 Family Background
Parents are the primary role-models in the early socialisation of children. Factors
such as parents' occupation, social status, birth order, and the relationship with
parents are associated with entry into entrepreneurship (Scherer et al., 1989).
Scholars argue that the existence of an entrepreneurial parent creates an
environment where development of entrepreneurial ability is encouraged and
success is stressed. Most empirical evidence indicates that, with a few exceptions
such as Zhang et al. (2013), individuals with prior entrepreneurial exposure are
more likely to start a business (Fairlie and Robb, 2006; Falck et al., 2012; Hisrich
and Peters, 1995; Mancuso, 1974; Robinson and Hunt, 1992; Shapero, 1981;
Zellweger et al., 2011).
3.3.2 Social, Situational and other Background Factors
Scholars indicate that social marginality, displacement events, gender, age and
prior experience have an influence on the likelihood of engaging in
entrepreneurship.
Historical and Theoretical Overview
60
Social Marginality
Entrepreneurship is often stimulated by social marginality (Deakins et al., 1997).
This entails that groups or individuals on the periphery of a social system are more
likely to behave entrepreneurially. These groups, perhaps because of their
religion, culture, ethnic beliefs or minority status, encounter a marginal social
position. This relative deprivation may trigger the impetus of such individuals to
move into entrepreneurship (Curran and Burrows, 1987; Stanworth and Curran,
1973). For instance, entrepreneurship in certain ethnic minorities is the approach
that the disadvantaged minorities take to alter their status quo (Casson, 1982). In
the UK, self-employment rate for ethnic groups such as Indian, Pakistanian,
Bangladeshi and Chinese is higher than that of the indigenous white group
(Blanchflower and Shadforth, 2007).
Situational Factors
Scholars indicate that sometimes a displacement event may trigger entry into
entrepreneurship. Such triggers include loss of a job, redundancy, or job
frustration (Shapero, 1975). The one possible alternative may be the launch of a
new enterprise. Entrepreneurs are sometimes seen as "misfits" (deviants) or
displaced individuals. An entrepreneur may also be someone unable to fit
comfortably into conventional organisational life (De Vries, 1977).
Entrepreneurship provides a productive outlet for enterprising energy.
3.3.3 Supportive Entrepreneurial Environment (Institutional Factors)
A legal, social, financial and economic environment that is supportive to
entrepreneurship is likely to promote business start-ups (Alvarez and Busenitz,
2001; De Clercq et al., 2011; Krueger and Brazeal, 1994; Penrose, 1959; Verheul
et al., 2002). Scholars argue that attitude and perceived capability toward
entrepreneurship are high when individuals can assess their own entrepreneurial
Historical and Theoretical Overview
61
ability within a supportive environment (Chen et al., 1998; Mauer et al., 2009).
Institutional theory is often the basis for exploring the effects of the environment on
entrepreneurial activity. Scholars suggest that there is a universal environment
outside of the entrepreneur’s mind which provides rules and norms that influence
an economy and its culture and policies (Busenitz et al., 2000; DiMaggio and
Powell, 1983; Scott, 2008). Institutions comprise the relevant factors in the
environment that provide rules and norms that either restrict or facilitate individual
actions (North, 1990). Thus, institutional theory can be employed to examine how
relevant formal and informal institutions enable or restrain entrepreneurship. Not
only do institutions affect the availability of opportunities, but also they affect how
opportunities are viewed by entrepreneurs.
“The kinds of information and knowledge required by the entrepreneur are in good part a consequence of a particular institutional context. Incentives/barriers are built in the institutional framework. The institutional framework will shape the direction of knowledge and skills which will be the decisive factor for the long run development of that society.” North (1990, p.78)
Albeit mainly considered at macro level, empirical studies in developed countries
find evidence that favourable regulatory, cognitive and normative institutions
positively influence the rate and type of entrepreneurial activity in an economy
(Bruton et al., 2010; Ebner, 2006; Falck et al., 2012; Rønning, 2006; Wicks, 2001).
Regulatory institutions include favourable laws and regulations for business
formation and operations as well as mechanisms supportive of individuals’
entrepreneurial efforts. Cognitive institutions refer to the level of shared knowledge
and information in society about venture creation, operations and growth. Lastly,
normative institutions refer to acceptability and admiration of innovation, creativity
and entrepreneurial careers in society (Busenitz et al., 2000; Engle et al., 2011;
Hofstede, 1984; Manolova et al., 2008; Reynolds, 2011; Spencer and Gomez,
2004).
Historical and Theoretical Overview
62
In summary, the sociological approach argues that entrepreneurial behaviour is
influenced by the immediate and wider environment (e.g family background,
situational factors and the wider environment comprising norms, shared
information and the regulatory framework). The critiques against this approach lie
in two fields. Firstly, it ignores the fact that individuals are different in terms of
personality and so irrespective of how favourable the environment might be not
everyone will choose to engage in entrepreneurship (Fayolle and Linan, 2014).
Secondly, the framework that incorporates formal and informal institutions for
assessing a country’s wider entrepreneurial environment (i.e. Busenitz et al.’s
2000 Country Institutional Profile for Entrepreneurship) has only been empirically
investigated at macro level to determine the type and rate of entrepreneurship in a
country; it is yet to be empirically investigated at micro level (Bruton et al., 2010).
3.4 Processual View of Entrepreneurship
A process is a series of actions, changes or functions bringing about an outcome
(Dictionary, 2011). Some scholars argue that the process involved in creating a
new venture or new value should be fundamental to the definition of
entrepreneurship. In other words, the processual view emphasises what
entrepreneurs do and how they do it, not who the entrepreneur is (Carter et al.,
1996; Gartner, 1990; Gartner, 1989b; Moroz and Hindle, 2010; Shane and
Venkataraman, 2000; Shane, 2003; Stevenson and Jarillo, 1990). Scholars argue
that entrepreneurship is about competitive behaviours that drive market processes
toward efficiency and effectiveness; entrepreneurship affects the market
processes through new alternative choice for consumers, pricing, and adjustments
in offerings of competitors (Casson, 1982; Davidsson, 2004; Hock-Beng, 1990;
Leibenstein, 1966).
Historical and Theoretical Overview
63
Scholars identify the actions (steps) an entrepreneur takes in exploiting an
opportunity (Schumpeter, 1934; Cole, 1965; Leibenstein, 1968; Vesper, 1980).
Gartner (1989) argues that entrepreneurship is not a fixed state of existence or
profession; rather entrepreneurship is a process that individuals undertake to
create organisations. This echoes views by other scholars suggesting that even
obvious entrepreneurs may exhibit their entrepreneurship only during a certain
phase of their career and/or concerning a certain part of their activities (Bruyat and
Julien, 2001; Carland et al., 1984; Carree and Thurik, 2010; Gartner, 1990;
Gartner, 1989b; Schumpeter, 1934).
Gartner (1985) identifies that there are six common activities in the process of
entrepreneurship: identifying a business opportunity; evaluating the opportunity;
accumulating resources; initiating the product/service; marketing the
product/service; building an organisation ; and, responding to government, society
and the market. Following Gartner’s (1985) work, Shane (2003) develops a
framework based on entrepreneurial opportunities (Figure 3.2). This framework is
the most comprehensive one that the field has and it itemises the phases of the
entrepreneurial process (Hindle and Al-Shanfari, 2011; Moroz and Hindle, 2010).
In addition, it implicitly acknowledges that each phase requires and depends on
different skills, actions and contexts. Lastly, entrepreneurship is a recursive
process (not linear) reflecting the typical actions and learning of entrepreneurs.
Historical and Theoretical Overview
64
Figure 3.2 - The Process of Entrepreneurship (Shane, 2003)
As indicated in Figure 3.2, the entrepreneurial process involves the identification
(discovery) and evaluation of an opportunity; the decision as to whether to exploit
it; the efforts to obtain the required resources; organising the required resources
into a new combination; and the development of a strategy for the new venture.
These different activities and phases are all influenced by individual, industry and
environmental factors (Shane, 2003). Therefore, entrepreneurship is a process
that involves the recognition, evaluation and exploitation of opportunities to
introduce new products or processes, access new markets or raw materials
through organising efforts that previously had not existed (Venkataraman, 1997;
Shane and Venkataraman, 2000; Schumpeter, 1934; Kirzner, 1973; Knight, 1921;
Millier, 1983).
In summary, the processual view is a recent approach to entrepreneurship. It
focuses on the process or series of actions/steps/activities that have to be taken to
transform an enterprising idea into an actual viable venture. It has become one of
the pillars for justifying that certain aspects of entrepreneurship can be
learnt/taught. The critique against this approach is that the link between the
process of entrepreneurship and the decision to engage with an entrepreneurial
Historical and Theoretical Overview
65
opportunity is not yet clear (Rideout and Gray, 2013). This is where the EI models
discussed in the next chapter fit in.
3.6 Conclusions
Based on the historical and theoretical perspectives discussed, this chapter has
highlighted the fact that entrepreneurship is a multi-dimensional phenomenon
(Gedeon, 2010; Matlay, 2005). Four major approaches can be employed to
understand entrepreneurship. These include: the economic approach (focusing on
the role of entrepreneurship in an economy), the psychological approach
(emphasising on the psychological factors associated with entrepreneurship), the
sociological approach (concentrating on the socio-cultural environment influencing
entrepreneurial behaviour), and the processual approach (focusing on the steps in
the process of entrepreneurship). Entrepreneurs are important because their
activities affect markets such as improved efficiency due to competition and
alternative choice for consumers (Atherton, 2004; Bygrave and Hofer, 1991;
Cunningham and Lischeron, 1991; Gartner et al., 1989; Mitton, 1989; Sexton and
Smilor, 1986; Shane and Venkataraman, 2000; Wilson et al., 2009). This leads to
stimulation of economic growth, employment generation, and increased incomes
that are important for any country (Birch, 1979; Criscuolo et al., 2014; de Kok and
de Wit, 2014; Gibcus et al., 2012; Hessels and van Stel, 2011). The next chapter
explores the role of EI in the entrepreneurship process and the evolution of the
associated theoretical models.
66
CHAPTER 4: INTENTIONALITY OF ENTREPRENEURSHIP
4.0 Introduction
The preceding chapter highlights four approaches to understanding
entrepreneurship. These include the economic approach, the psychological
approach, the sociological approach, and the processual approach. This chapter
firstly explores the role of entrepreneurial intention (EI) in the process of
entrepreneurship (4.1). Secondly, it highlights the prominent theoretical models of
EI and empirical studies in this field (4.2). Thirdly, it identifies areas for further
research to facilitate stakeholders’ comprehensive understanding of the
development of EI (4.3).
4.1 The Role of Intention in the Process of Venture Creation
Several scholars indicate that entrepreneurship is a process involving the
discovery, evaluation and exploitation of opportunities to introduce new products
or processes, access to new markets and raw materials through organising efforts
that previously have not existed (Bruyat and Julien, 2001; Gartner, 1985; Moroz
and Hindle, 2010; Sarasvathy, 2001; Sarasvathy and Venkataraman, 2011;
Shane, 2003). Shane’s (2003) ‘nexus of enterprising individual–entrepreneurial
opportunity’ model is the most comprehensive model of the entrepreneurship
process. Other models such as Gartner’s (1985) framework of new venture
emergence, Bruyat and Julien’s (2001) model of new value creation, and
Sarasvathy’s (2001) dynamic model of effectuation also show a picture of the
entrepreneurial process.
Before an entrepreneurial opportunity is consciously searched for, or after the
entrepreneurial opportunity is inadvertently stumbled upon, the would-be
Intentionality in Entrepreneurship
67
entrepreneur should have an intention to engage with the opportunity (Krueger Jr,
2007a). Entrepreneurship includes transforming a new idea into something
valuable (Green, 2009; Schramm, 2006). Green (2009) states that
entrepreneurship involves three components: a new idea located in an
entrepreneurial opportunity, its implementation into an enterprise, and the market’s
acceptance of the product. Understanding the link between ideas and action is
critical for understanding the entrepreneurial process (Bird, 1988; Bird, 1992;
Krueger and Carsrud, 1993). However, an individual cannot engage with an
entrepreneurial opportunity without an intention to do so. EI is a representation of
a future course of action. It is not simply an expectation or prediction of future
actions but a proactive commitment (Bandura, 2001; Thompson, 2009).
Intentionality is a state of mind directing a person's attention, experience and
actions toward a specific object (goal) or path. Scholars indicate that intention is
the most immediate antecedent of a given behaviour (Ajzen, 1991; Bird, 1988;
Fishbein and Ajzen, 1975; Zhao et al., 2010a). Although behaviour can result from
unconscious and unintended antecedents, what is of interest here is conscious
and intended act, the founding of a firm. Even though some entrepreneurial ideas
begin with inspiration, intention is required for sustained attention and action.
Entrepreneurs’ intentions guide their goal setting, communication, commitment,
organisation and other kinds of work and effort in the entrepreneurial process
(Bird, 1988; Carter et al., 1996; Forbes, 1999; Katz, 1992; Katz and Gartner, 1988;
Learned, 1992; Rotefoss and Kolvereid, 2005).
Is all Entrepreneurial Behaviour Planned? Some scholars have argued against exaggerating the role of intentions in human
planned and conscious behaviour (Pickering, 1981; Wegner, 2002). For instance,
Davidsson (2004) suggests that there are two main routes to starting one’s own
Intentionality in Entrepreneurship
68
business. Firstly, there are individuals who indeed start with an intention followed
by search, evaluation and then exploitation of a specific business opportunity.
Secondly, there are individuals who may, by serendipity, develop a product that
potentially has demand in the market. This second group is unlikely to report an
intention well in advance of actually starting the business (Davidsson, 2004).
However, the majority of scholars suggest that although serendipity can
sometimes lead to entrepreneurship, EI is fundamental to the entrepreneurial
process (Katz and Gartner, 1988; Kautonen et al., 2013; Krueger Jr, 2007b;
Rotefoss and Kolvereid, 2005; Shapero and Sokol, 1982; Webster, 1977). This is
because empirical evidence indicates that EI has proved to be an important
antecedent of entrepreneurial behaviour (Carr and Sequeira, 2007; Hmieleski and
Corbett, 2006; Wilson et al., 2007). All forms of entrepreneurship and especially
new firms set up by individuals, or groups of individuals, begin with some degree
of planned behaviour (Krueger JR et al., 2000; Shook et al., 2003; Thompson,
2009). The GEM indicates that EI correlates positively with business creation in a
society (Kelley et al., 2012). Other empirical evidence indicates that individuals
with higher EI are more likely to start a business than those with lower or no EI
(Henley, 2007; Kautonen et al., 2013).
4.2 Review of Prominent Entrepreneurial Intention Models
Several conceptual models exploring determinants of EI (Bird, 1988; Boyd and
Vozikis, 1994; Davidsson, 1995; Krueger and Carsrud, 1993; Krueger, 1993;
Krueger and Brazeal, 1994; Lim et al., 2010; Lüthje and Franke, 2003) are
primarily based on Shapero and Sokol’s (1982) entrepreneurial event (SEE)
model, Ajzen and Fishbein’s (1991, 2002, 2005) theory of reasoned action and
planned behaviour (TPB), as well as Bandura’s (1986) social learning theory of
self-efficacy. Seminal works such as Shapero and Sokol (1975, 1982), Bird
Intentionality in Entrepreneurship
69
(1988), Katz and Gartner (1988), Learned (1992), Katz (1992), Forbes (1999) as
well as Fishbein and Ajzen (1975) make notable theoretical contributions for
understanding the development of EI. To explore how EI models have evolved,
three key models are discussed: Bird’s (1988) contexts of intentionality model,
Shapero and Sokol’s (1982) entrepreneurial event model, and Ajzen’s (1991)
theory of planned behaviour.
4.2.1 Bird (1988): The Contexts of Intentionality
Bird’s (1988) model, developed based on interviews with novice and experienced
entrepreneurs, attempts to explain and predict entrepreneurial behaviour. Bird
argues that an individual’s intention determines whether a venture will be launched
or not. It also determines the form and direction of an organisation at its inception.
Additionally, organisational success, development, growth, and change are based
on EI.
“Entrepreneurial intentions, the entrepreneurs' states of mind that direct attention, experience, and action toward a business concept, set the form and direction of organisations at their inception. Subsequent organisational outcomes such as survival, development (including written plans), growth, and change are based on these intentions… the intentional process begins with the entrepreneur's personal needs, values, wants, habits, and beliefs, which have their own precursors. These five antecedents result in intra-psychic activities (i.e. creating and maintaining a temporal tension, sustaining strategic focus, and developing a strategic posture) which are at the core of intentional and behavioural outcomes which contribute to the creation of a new organisation and, in turn, affect the entrepreneur's needs, values, wants, habits, and beliefs.” Bird (1988, p.442)
Bird indicates that her model can be applied to studying the creation of a new
venture or the development and growth of an existing venture. Firstly, she
suggests that the intentionality process is affected by a combination of both
personal and contextual factors. Personal factors include prior experience, history,
personality and abilities while contextual factors include social, political and
economic variables along with changes in the markets and regulatory framework
(Bird, 1988). These personal and contextual factors create the context of
Intentionality in Entrepreneurship
70
intentionality (Figure 4.1). Secondly, she argues that the personal and contextual
factors influence the person's rational, analytical thinking (cause and effect
thinking) and intuitive, holistic thinking which structure intention and the
consequent actions. These cognitive processes underlie formal business plans,
opportunity analysis, resource acquisition, goal setting and the most observable
goal-directed behaviour (Boyd and Vozikis, 1994).
Source: Bird (1988)
Figure 4.13- Contexts of Intentionality Model
The strength of Bird’s model is twofold. Firstly, it explicitly recognises that without
intention, an organisation cannot start, let alone succeed (Katz and Gartner 1998).
Secondly, it explicitly indicates that personal and contextual factors positively
influence the formation and modification of EI (Davidson, 2004; Hindle, 2007).
However, in order to explain why some people and not others engage in
entrepreneurship, there are a lot more factors that need consideration within and
outside the ambit of personal and contextual factors. Additionally, the model hardly
suggests any mechanism(s) through which individual and contextual factors
influence EI. Consequently, Boyd and Vozikis (1994) attempt to modify Bird's
model by incorporating factors that may moderate the influence of personal and
Intentionality in Entrepreneurship
71
contextual factors on EI such as attitudes and self-efficacy (Figure 4.2). Their
proposition is based on Bandura (1977)’s concept of self-efficacy derived from
social learning theory. Self-efficacy refers to a person's belief in his or her
capability to perform a given task. Choices, aspirations, effort and perseverance
are influenced by perceptions of one's own capabilities. Boyd and Vozikis posit
that perceived self-efficacy and attitudes will moderate the relationship between EI
and the likelihood that these intentions will result in action.
Source: Boyd and Vozikis (1994)
Figure 4.24- Revised Model for Contexts of Intentionality
Following Bird’s revised model, scholars like Luethje and Franke (2003) and Nabi
et al. (2010) empirically examine the influence of personality factors (i.e. locus of
control and risk taking propensity) as well as perceived barriers and support in the
entrepreneurial environment on EI. They conclude that while personality factors
influence EI indirectly through attitude toward entrepreneurship, contextual factors
influence EI directly. However, these studies do not take into account
entrepreneurial self-efficacy, entrepreneurship education, and a broad range of
institutional factors (Bruton et al., 2010; Boyd and Vozikis, 1994).
Intentionality in Entrepreneurship
72
4.2.2 Azjen (1991): The Theory of Planned Behaviour
Ajzen’s (1991, 1985) theory of planned behaviour (TPB) follows the theory of
reasoned action on beliefs, attitudes and intentions as determinants of human
behaviour (Ajzen and Fishbein, 1980; Ajzen, 2011a; Ajzen, 2011b; Bandura, 1982;
Bandura, 1993; Bandura, 1977; Fishbein and Ajzen, 1975). The TPB indicates that
intention is the best predictor of an individual’s behaviour. This is because
intention is an indication of how hard an individual is willing to try, of how much of
an effort he or she is planning to exert, in order to perform the behaviour. As a
general rule, the stronger the intention to engage in a behaviour, the more likely
should be its performance (Ajzen, 1991). The TPB also suggests that intention
toward a specific behaviour has three immediate antecedents (Figure 4.3):
personal attitude towards the behaviour (PA), subjective norm (SN) and perceived
behavioural control (PBC). First, “attitude toward the behaviour is the degree to
which a person has a favourable or unfavourable evaluation of the behaviour in
question” (Ajzen,1991, p.188). ‘Do I perceive that this would be a good thing to
do?’ With regard to entrepreneurship, the intention of launching a new business
will be influenced by how personal values and attitudes have been shaped over
time.
Second, subjective norm refers to “the perceived social pressure to perform or not
to perform a particular behaviour” (Ajzen, 1991, p.188). ‘Would people important to
me consider this action as a good move?’ How friends, relatives or colleagues
consider a particular behaviour will affect a person’s perception. A study by Falck
et al. (2012), based on data from the Organisation for Economic Cooperation and
Development (OECD) countries, finds that young people with either a) a parent
who is an entrepreneur or b) school peers/friends that have at least one parent
who is an entrepreneur, report higher EI.
Intentionality in Entrepreneurship
73
Source: (Ajzen, 1991)
Figure 4.35-- Theory of Planned Behaviour Model
Thirdly, “perceived behavioural control refers to the perceived ease or difficulty of
performing the behaviour of interest…and it is assumed to reflect past experience
as well as anticipated impediments and obstacles” (Ajzen, 1991, p.188). ‘Could I
do it if I want to?’ With regard to entrepreneurship, it relates to the perception of
technical competencies required, the financial risks, the administrative burden and
the possessed resources and abilities. Krueger and Dickson (1994) indicate that
the higher the perceived behavioural control in relation to new venture creation,
the higher the EI.
The TPB further posits that subjective norm, attitude toward the behaviour and
perceived behavioural control will mediate the effects of any other factors on EI
(Ajzen, 2011a). Several studies find empirical support for the TPB in relation to EI
(Iakovleva et al., 2011; Krueger JR et al., 2000; Liñán and Chen, 2009; Liñán et
al., 2011a; Liñán et al., 2011b; Siu and Lo, 2013).
Criticisms against the TPB are many. Some scholars reject it outright as an
adequate explanation of human social behaviour. These scholars argue that
conscious and rational choice is not the only signficant basis for an individual’s
Intentionality in Entrepreneurship
74
behaviour (Wegner, 2002) and view much human social behaviour as driven by
implicit attitudes (Greenwald and Banaji, 1995) as well as other unconscious
mental processes (Aarts and Dijksterhuis, 2000; Brandstätter et al., 2001;
Uhlmann and Swanson, 2004). Most critics, however, accept the theory’s basic
assumption on reasoned action but question its adequacy (Davidsson, 2004). This
is because, based on empirical studies, the correlations between attitudinal
antecedents and intention as well as those between intention and actual behaviour
range from 40% to 60% (Ajzen, 2011). This means that the explanatory power of
the elements in the TPB is significant but limited. The overall criticism of the TPB
is that it neither identifies nor examines factors leading to the formation, and
perhaps modifications, of the three antecedents of EI, hence, the need for
research that explores the possible precursors (Ajzen and Fishbein, 2005; Ajzen,
2011a; Ajzen, 2011b; Davidsson, 1995; Davidsson, 2004; Fishbein and Ajzen,
2011; Hindle, 2007; Hindle and Al-Shanfari, 2011).
4.2.3 Shapero and Sokol (1982): Entrepreneurial Event Model
Shapero and Sokol’s model posits that an entrepreneurial event is primarily a
function of perceived desirability and feasibility. While perceived desirability
depends on the individual’s value (attitude) and social systems in which he/she is
involved, perceived feasibility is associated with an individual’s ability and
competence as well as likelihood of support from stakeholders (Shapero and
Sokol, 1982). These perceptions determine whether or not the person chooses to
engage in company formation (Figure 4.4).
Intentionality in Entrepreneurship
75
Source: (Shapero and Sokol, 1982)
Figure 4.46- Shapero and Sokol’s Entrepreneurial Event Model
Shapero and Sokol explain perceived desirability as the degree to which a person
considers starting a business attractive. Perceived feasibility is the degree to
which one believes he/she is capable of starting a business. Shapero and Sokol
explain “propensity to act” as the personal disposition to act on one's decisions,
thus, reflecting volitional aspects of intentions (“I will do it”). They argue that it is
hard to envisage well-formed intentions without some propensity to act.
Conceptually, propensity to act on an opportunity depends on control perceptions:
that is, the desire to gain control leading to actions. Shapero and Sokol further
suggest that propensity to act is equivalent to internal locus of control (Chen et al.,
1998).
Shapero and Sokol's model assumes that every individual has a tendency to
continue with his or her current behaviour until one encounters a “displacement
event”. Usually a displacement is either a positive (pull) or negative (push) event.
The bottom line is that a displacement precipitates a change in behaviour where
the decision maker seeks the best opportunity available from a set of alternatives.
For stance, completion of undergraduate studies compels graduating students to
consider the best opportunity available among a set of alternatives. Graduating
Intentionality in Entrepreneurship
76
students’ alternatives typically include organisational employment, starting a
business or embarking on further studies. Such a decision is made based on what
an individual perceives to be desirable and feasible (Krueger et al, 2000; Shapero
and Sokol, 1982).
As with the TPB, exogenous factors do not directly affect an individual’s intention
or behaviour. They operate through perceived desirability and feasibility. Empirical
evidence indicates that perceived feasibility and desirability as well as the
propensity to act explain over half of variance of EI (Krueger JR et al., 2000;
Krueger, 1993; Peterman and Kennedy, 2003).
4.2.4 Comparison of TPB and SEE Models
The theory of planned behaviour (TPB) and Shapero and Sokol’s entrepreneurial
event (SEE) models have been found by several studies as overlapping in two
aspects. Firstly, the SEE model’s perceived desirability is equivalent to the TPB
model’s attitude towards the behaviour and subjective norms. Secondly, the SEE
model’s perceived feasibility is not only equivalent to the TPB model’s perceived
behavioural control but also entrepreneurial self-efficacy (Bandura, 2001; Chen et
al., 1998; De Noble et al., 1999; Krueger and Brazeal, 1994; McGee et al., 2009).
Furthermore, both models suggest that contextual factors would influence intention
through attitudes and self-efficacy (Fayolle and Gailly, 2004; Fayolle et al., 2006b;
Krueger JR et al., 2000; Peterman and Kennedy, 2003; Zhao et al., 2005).
However, there is a shortage of studies investigating these aspects in an
integrative manner (Davidsson, 2004; Fayolle and Liñán, 2014). Some scholars do
not bother to consider contextual factors because their effects are already
reflected in perceived feasibility and desirability anyway (Krueger JR et al., 2000).
It should also be noted that various studies use different measures as there are no
standard measurement instruments for EI and its attitudinal antecedents (Liñán
Intentionality in Entrepreneurship
77
and Chen, 2009; Thompson, 2009). This hinders the theory development. In an
attempt to integrate the TPB and SEE models, Schlaegel and Koenig (2014)
conduct meta-analysis of 92 empirical studies. The authors find that, when using
the TPB, the combined influence of attitude to the behaviour (ATB), subjective
norms (SN), entrepreneurial self-efficacy (ESE), and perceived behavioural control
(PBC) on EI is significant. When using the SEE model, propensity to act,
perceived desirability and feasibility have a significant combined influence on EI.
When all the attitudinal determinants from the two models are included in the
analyses, the increase in combined influence is also significant. The authors
conclude that EI is primarily a function of perceived feasibility and desirability of
entrepreneurship, confirming similar conclusions by other scholars (Fitzsimmons
and Douglas, 2011).
4.3 Further Development of the EI Model Required
Since the foundational works by Shapero (1975), Shapero and Sokol (1982), Bird
(1988), as well as Katz and Gartner (1988), several empirical studies have
focused on EI. Yet there has been growing concern about the inconclusive
findings of the relationship between EI and its determinants. Scholars indicate that
the field is fragmented and lacks theoretical clarity and empirical evidence, and
they encourage research to develop integrative models of EI, which may enhance
the explanatory power and theoretical clarity (Fayolle and Liñán, 2014; Krueger,
2009; Schlaegel and Koenig, 2014; Shook et al., 2003).
Specifically, integrative models are requested to test institutional and individual
factors as well as educational interventions in different contexts (Dohse and
Walter, 2012; Fayolle and Liñán, 2014; Nabi et al., 2010; Nabi and Liñán, 2011;
Rideout and Gray, 2013; Siu and Lo, 2013). It is also necessary to understand
Intentionality in Entrepreneurship
78
how perceived feasibility and desirability are formed. In the literature, there is a
continued critique against the basic EI model that it neither identifies nor examines
factors leading to the formation, and perhaps the modification, of perceived
feasibility and desirability. Indeed although the basic EI model has empirically
shown significant explanations, it does not show the full picture. Other individual
and environmental factors that may have a role in new venture creation should be
explored (Ajzen, 2011b; Alvarez et al., 2011; Bae et al., 2014; Davidsson, 1995;
Davidsson and Wiklund, 1997; Davidsson, 2004; Fayolle et al., 2006a; Rideout
and Gray, 2013; Siu and Lo, 2013).
Furthermore, scholars observe that determinants of EI are researched in isolation
from each other. Hence, scholars call for studies that examine how factors at the
individual and institutional levels are combined in shaping EI (De Clercq et al.,
2011; Fayolle and Liñán, 2014; Hitt et al., 2007; Hitt et al., 2007; Krueger, 2009;
Shane and Venkataraman, 2000; Shook et al., 2003; Walter et al., 2011). A cross-
level approach may address inconsistent findings on determinants of EI (Cope,
2005; Fayolle and Liñán, 2014; Gartner, 1989a; Hindle et al., 2009; House et al.,
1996; Krueger, 2009; Martínez et al., 2010; Mitchell et al., 2007; Wang and Chugh,
2014).
Reflecting on EI Models and Choice for This Study Bird’s (1988) model indicates that personal and contextual factors positively
influence the formation of EI. However, the model hardly suggests any
mechanisms through which individual and contextual factors influence EI. In
addition, the model has not been empirically validated/tested. Boyd and Vozikis
(1994) suggest a revision to Bird’s model to include attitudes, perceptions and
beliefs as moderators. However, Boyd and Vozikis’ revision does not include the
influence of EE. Neither has it been empirically tested. Further to the empirical
Intentionality in Entrepreneurship
79
work by Krueger et al. (2000) assessing the relative usefulness of the TBP and
SEE models in predicting EI, Schlaegel and Koenig (2014) conduct meta-analysis
of 92 studies. The authors conclude that EI is primarily a function of perceptions of
feasibility and desirability of entrepreneurship, confirming similar conclusions by
other scholars (Fitzsimmons and Douglas, 2011; Linan et al., 2011). Therefore this
study chooses to employ the SEE model as the foundation for exploring
determinants of EI. As indicated earlier, the SEE model posits that perceptions of
feasibility and desirability of a particular behaviour are the immediate antecedents
of intention to engage in that behaviour. And that the intention is the best predictor
of the behaviour. However, to address the limitations of the model as indicated
earlier, Schlaegel and Koenig (2014, p.320) observe that “it would be meaningful
for future research to explore the contingent roles of formal institutional context
(laws, regulations and policies) as well as the informal institutional context (culture,
norms and values)… to offer great insights into the context-specific development
of EI’’. Similarly other scholars call for development and testing of integrative
multi-level models that consider individual and contextual factors to enhance
explanatory power and theoretical clarity.
4.4 Conclusions
This chapter has discussed the role of EI in the process of entrepreneurship. All
forms of entrepreneurship and especially new firms set up by individuals or groups
begin with some degree of planned behaviour. EI is an important measure of
potential entrepreneurship in a society. However, there has been growing concern
about the inconclusive findings on EI and its determinants. Scholars recommend
future research should build up and test integrative models of EI to understand this
core concept of entrepreneurship. The next chapter reviews literature on
Intentionality in Entrepreneurship
80
entrepreneurship education (EE) and its role in influencing EI and the consequent
behaviour.
81
CHAPTER 5: ENTREPRENEURSHIP EDUCATION – IMPORTANCE, TYPES
AND EFFECTS
5.0 Introduction
The preceding chapter discusses the role of entrepreneurial intention (EI) in the
process of entrepreneurship. This chapter reviews literature on entrepreneurship
education (EE) and its role in the development of entrepreneurial skills, knowledge
and attitudes that are expected to influence entrepreneurial intention and
behaviour. Specifically, the chapter discusses the importance of entrepreneurship
education (5.1), the types of entrepreneurship education (5.2), and the impact of
entrepreneurship education on EI (5.3).
5.1 Importance of Entrepreneurship Education
Generally, education is a lifelong process of developing the powers of reasoning
and judgement as well as preparing individuals for life (Matheson, 2008).
Specifically, formal education is a structured process in which knowledge, skills,
attitudes, character and behaviour of a person are shaped and moulded (Kolb et
al., 2001; Krathwohl and Bloom, 2002; Matheson, 2008). Scholars indicate that
education is a mirror of society since it reflects societal priorities. Therefore,
whenever the needs of society change, its education system changes accordingly.
Since education’s aims and methods depend on the nature of the society, certain
factors are expected to shape the emphases of education. These may include
socio-cultural conditions, geographical position, economic conditions,
political/government policies as well as philosophy (Matheson, 2008; Wilson et al.,
2009; Gibb, 2007).
Entrepreneurship Education
82
Wilson et al. (2009) claim that entrepreneurship is the engine fuelling innovation,
employment generation and economic growth. Considering the power that
education has in developing the skills that generate an entrepreneurial mind-set
and in preparing future leaders for solving more complex, interlinked and fast-
changing problems, it is clear that enterprise education is important (Wilson et al.,
2009). Mitra (2011) suggests that there is need to integrate the acquisition of
entrepreneurial competencies and 'soft skills' such as creativity, initiative and
persuasion in the curriculum across all ages and subjects. This implies a shift from
the traditional emphasis on evaluating the ideas of others to generating and
implementing one’s own ideas (Mitra, 2011). Mitra (2011) further notes that
whatever the definition of entrepreneurship, it is closely associated with change,
creativity, knowledge, innovation and flexibility, which are important sources of
competitiveness in an increasingly globalised world economy (Mitra, 2011). The
world is changing fast. The number of people working in small firms or who are
self-employed has grown sharply, while jobs in the public sector and large firms
are cut back (Galloway et al., 2005; Rae et al., 2012). These trends seem set to
continue. Young people seeking jobs need to be more flexible and entrepreneurial.
Even in larger firms, public and voluntary sectors, entrepreneurial skills are more
highly valued than they were in the past (CBI - NUS, 2011; Davies, 2002). Thus,
the education systems are playing an important role in developing people for the
changing world of work and employability.
Specific Pressures Moulding the Need for Entrepreneurial Skills In the challenging economic environment, entrepreneurial skills can be beneficial
(Collins et al., 2004b; Robertson et al., 2003; Woodier-Harris, 2010). The
challenges continue to create greater uncertainty and complexity confronting
people at four levels: global, societal, organisational, and individual levels (Fayolle,
2007; Gibb, 2007). Firstly, at the global level, the reduction of trade barriers to
Entrepreneurship Education
83
international business, standardisation of goods and services, in conjunction with
the advancements in technology, all combine to provide more competition,
opportunities as well as uncertainties. Secondly, in countries with open market
economies, privatisation, reduced welfare and social security spending, high
unemployment and mounting environmental concerns, there are greater
complexities and uncertainties. Thirdly, at the organisational level, the need for
restructuring and re-engineering for efficiency and effectiveness, as well as the
growing demand for flexibility in the workforce, lead to an uncertain climate. Lastly,
at the individual level, there is a wider variety of sources of employment
uncertainty such as more responsibility at work and more stress, more short term
contracts and few employment opportunities. Figure 5.1 reflects the interaction of
these pressures in creating complexity and uncertainty at all levels of human
endeavour.
Sources: (Gibb and Cotton, 1998a; Gibb, 2007; Gibb and Cotton, 1998b)
Figure 5.17- Education and the Changing World
Given the foregoing sources of uncertainty and complexity, the need for an
entrepreneurial response is apparent. Entrepreneurial knowledge, skills, attributes,
values and behaviours may enable people to deal with challenges and
uncertainties. Furthermore, whatever their career choice or personal situation,
through the study of entrepreneurship, individuals will be able to benefit from
Entrepreneurship Education
84
learning innovative approaches to problem solving, adapting to change, and
becoming more self-reliant and developing their creativity (Gibb, 2007). There is
no doubt that under any economic climate such learning could have far reaching
benefits for society. It could be argued, therefore, that the need for
entrepreneurship education and training has never been greater (Hytti and
O’Gorman, 2004).
Moreover, national competitive advantage is increasingly dependent on the skill
base of the workforce and more specifically on the ability for both individuals and
firms to engage in innovative and new economic activities (Child and McGrath,
2001; Hytti and O’Gorman, 2004). This has resulted in the need for general
enterprising skills required for innovative, proactive and problem solving behaviour
as well as specific entrepreneurial skills required for new venture creation,
management and growth (Gibb, 2007; Henry, 2013; Williams and Turnbull, 1997).
Thus, in many countries, enterprise education is becoming an important part of
industrial policy and education policy.
5.2 Types of Enterprise and Entrepreneurship Education
Scholars argue that there is a difference between ‘enterprise’ and
‘entrepreneurship’ and similarly between ‘enterprise’ and ‘entrepreneurship’
education. For example, scholars often ask the question “are they trying to
develop enterprising graduates or entrepreneurial graduates?” (Kirby, 2004). This
query implies that it is necessary to distinguish between the broader meaning of
enterprise education and the narrow meaning of entrepreneurship education
(Henry et al., 2003). Specifically, some scholars perceive enterprise education as
a process of equipping students (or graduates) with an enhanced capacity to
generate ideas and the skills to proactively make them happen. Others believe
Entrepreneurship Education
85
entrepreneurship education is a process that equips students with the additional
knowledge, attributes and capabilities required in the context of setting up,
managing and growing a new venture or business (QAA, 2012; Rae et al., 2012;
Williamson et al., 2013). Numerous scholars (Hills, 1988; Jamieson, 1984;
Mcmullan and Long, 1987) highlight the variety of approaches/paradigms of
entrepreneurship education with variations in content, learning methods and goals.
These approaches broadly comprise education ‘through’ enterprise, education ‘in’
entrepreneurship, education ‘about’ entrepreneurship, and education ‘for’
entrepreneurship (Béchard and Grégoire, 2005; Blenker et al., 2011; Honig, 2004).
5.2.1 Enterprise and Enterprise Education
Enterprise is defined as the application of creative ideas and innovations to
practical situations (Rae et al., 2012). It combines creativity, idea development,
initiative, independence and problem solving with communication and practical
action. This definition is distinct from the generic use of the word in reference to a
project or business venture (Bridge et al., 2009; Gibb, 2000). Education “through”
enterprise embraces teaching approaches/styles which require idea generation
and action-based learning (entrepreneurial situations) as part of the education
process. Consequently, enterprise values, attitudes and behaviours are learnt
through the process (De Faoite et al., 2003; Hannon, 2005; Matlay and Mitra,
2002). Gibb (2007) provides a framework of entrepreneurial behaviours, skills,
attributes and values that enterprise education should attempt to
develop/enhance.
Entrepreneurship Education
86
Table 5.16- Entrepreneurial Behaviours, Attributes, Skills, Values and Beliefs
1. Entrepreneurial Behaviours
opportunity seeking and grasping
taking initiatives to make things happen
solving problems creatively
managing autonomously
taking responsibility for, and ownership of, things
seeing things through
networking effectively to manage interdependence
putting things together creatively
using judgement to take calculated risks
3. Entrepreneurial Attributes
achievement orientation and ambition
self-confidence and self-belief/ esteem
perseverance
high internal locus of control (autonomy)
action orientation
preference for learning by doing
hardworking
determination
creativity
3. Entrepreneurial Skills
creative problem solving
persuading
negotiating
selling
proposing
holistically managing business/ projects/ situations
strategic thinking
intuitive decision-making under uncertainty
networking
emotional intelligence
4. Values and Beliefs Entrepreneurship is embodied in sets of values and beliefs relating to:
ways of doing things
ways of seeing things
ways of feeling things
ways of communicating things
ways of organising things
ways of learning things
Source: (Gibb, 2007)
As shown in Table 5.1, the purpose of education ‘through’ enterprise is to develop
entrepreneurial behaviours, skills, attributes and values of individuals. This is
necessary for coping with change and innovation so that individual and
organisational goals can be achieved. This conceptualisation embraces
organisations and work of all kinds; it is not a function of business activity alone.
There are social entrepreneurs, educational entrepreneurs, religious
entrepreneurs, and entrepreneurs in a range of nongovernmental organisations.
Thus, it is possible to encourage entrepreneurial behaviour through action-based
learning within the context of the standard curriculum subjects such as language
and literature, mathematics, geography, history and science. Furthermore,
scholars often acknowledge that while education should play its role, the
development of an individual is influenced by many factors at different stages of
life (Falck et al., 2012; Hindle, 2002; Hindle and Al-Shanfari, 2011). These include
Entrepreneurship Education
87
parental education, family values and goals, interactions with the wider social and
economic environment, role models and the education one receives at primary,
secondary and tertiary levels (Dohse and Walter, 2012; Gibb, 2007; Gibb, 2002;
Kuratko, 2003).
5.2.2 Entrepreneurship and Entrepreneurship Education
Entrepreneurship is the application of enterprise skills and ideas specifically to
creating and growing a venture by identifying, evaluating and exploiting
opportunities (QAA, 2012; Rae et al., 2012). Entrepreneurship education (EE) is
different from enterprise education in two major ways. Firstly, unlike enterprise
education which refers to the process of equipping students with an enhanced
capacity to generate ideas and the skills to proactively make them happen, EE
applies these skills in the specific context of new venture creation. Therefore, EE
equips students with the additional knowledge, attributes and capabilities required
in setting up a new venture, usually a business. Secondly, while enterprise
education can be provided as a pedagogical approach in any subject, EE is only
provided through a module/course/programme that focuses on starting, managing
and growing a new venture (Draycott and Rae, 2011; QAA, 2012; Williamson et
al., 2013).
Three types of entrepreneurship education can be identified. Firstly, education ‘in’
entrepreneurship deals mainly with entrepreneurship and management
development training for nascent and established entrepreneurs. It focuses on
developing knowledge and skills for ensuring survival, growth and future
development of the business (Blenker et al., 2011; Kirby, 2004). Secondly,
education ‘about’ entrepreneurship informs students about the nature of business,
innovation and small business management and their role in economic activity
(Levie, 1999). It deals mostly with awareness creation and has the specific
Entrepreneurship Education
88
objective of educating students on the various aspects of setting up and running a
business mostly from a theoretical perspective (Gibb and Hannon, 2005). These
courses tend to be taught in a traditional manner through lectures, textbooks, and
essays, and are assessed in assignments and end of course/module written
examinations (Edwards and Muir, 2005). Such courses may encourage students
to consider entrepreneurship as a career (Kirby, 2004). Thirdly, education ‘for’
entrepreneurship deals more with the preparation and development of
competencies and understanding of the practical processes in new venture
creation, management and growth (Levie, 1999). Participants are encouraged to
set-up and run their own businesses. These courses have educational activities
that stimulate and promote the development of entrepreneurial knowledge, skills
and attitudes through self-directed experiential learning. The practical educational
activities may include learning through projects, experiences, placement in a small
business, appropriate work placement and simulated entrepreneurial activity
(Cresswell, 1999; De Faoite et al., 2003; Henry et al., 2005a).
5.2.2.1 Debate on whether or not Entrepreneurship can be Taught
The foregoing discussion on the different types of entrepreneurship education
implies that there is ‘no one size fits all’; when designing a module/course or
programme, there is a need to consider the intended learning outcomes/objectives
as well as the learning content and approaches that would best achieve those
outcomes (Blenker et al., 2011; Hills, 1988). The focus of the current research is
education ‘for’ and ‘about’ entrepreneurship because the major aim is to
investigate the effect of EE on the intention to start a business after graduation.
Thus, for this research, EE is the transfer of knowledge and skills about how, by
who and with what to create future goods and services (Hindle, 2007; Martinez et
al., 2010).
Entrepreneurship Education
89
Over the years, educators and professionals’ perspectives have evolved beyond
the myth whether entrepreneurs are born or made. There is a perception that
some innate abilities/personality attributes relevant to entrepreneurial tasks and
roles cannot be taught (Bolton and Thompson, 2002; Hindle, 2007; Klein and
Bullock, 2006). However, it has become clear that certain aspects of
entrepreneurship such as the practical processes of new venture formation,
acquisition and management of resources can be taught (Hindle, 2007; Klein and
Bullock, 2006; Kuratko, 2003). Additionally, other aspects such as opportunity
identification, creativity and alertness can also be enhanced through experience.
For example, scholars find that experienced entrepreneurs are better at identifying
opportunities (Klein and Bullock, 2006; McGrath and MacMillan, 2000).
Over the decades, not only has EE established itself as a legitimate field of
research, it has also been recognised as a taught discipline area within higher
education (Henry, 2013; Matlay, 2009; Pittaway and Cope, 2007). Nevertheless,
there remains considerable debate around what should be taught, how it should
be taught and who should actually teach it (Hindle, 2007; QAA, 2012; Wilson et al.,
2009). Additionally, alongside the idea of what, how and who, the fundamental
question of why entrepreneurship should be taught (related to “can
entrepreneurship be taught”) keeps re-emerging (Henry et al., 2005a; Henry et al.,
2005b; Henry, 2013). Some scholars argue that the why question is now obsolete,
having been asked and answered in earlier seminal works (Clark et al., 1984;
Drucker, 1985; Kuratko, 2005). Two major strands of rationale are established.
Firstly, EE helps students to become more enterprising thereby preparing them for
the uncertain and complex world of work (Gibb and Cotton, 1998). Secondly, EE
helps develop individuals’ capacity for generating and analysing business ideas,
identifying and exploiting opportunities (CBI - NUS, 2011; QAA, 2012; Wilson et
Entrepreneurship Education
90
al., 2009). In relation to the legitimate question of how entrepreneurship could be
taught (Henry, 2013; Kuratko, 2003; Ronstadt, 1990), some scholars suggest that
entrepreneurship is something one learns by doing (Van der Sijde, 2008). David
Birch, the prominent American scholar whose work first produced the evidence
that small and new businesses created the lion’s share of employment (80 - 85%
of all new jobs from 1969 to 1975 in the US), said:
“…However, if you want to encourage entrepreneurship, it should be through some kind of apprenticeship. That would be a wonderful experience.” (quoted in Aronsson, 2004, p.289)
The above quote indicates that entrepreneurship may not be taught and learnt
adequately through the traditional way of delivering. There is a need to emphasise
a practical mode of instruction; there should be opportunities for learning in an
active environment where the individual has hands-on business environment
experience (Aronsson, 2004). However, the scope for practical experience in
university education is limited; ‘…to teach individuals to become not only more
enterprising but also businessmen and women …is an undertaking that in both
time and scope is beyond the capabilities of an academic business school’
(Johannisson, 1991). Consequently, other scholars argue that entrepreneurship
theory and practice are interwoven (Fiet, 2001; Rae, 2007b). Hindle (2007)
suggests that in EE, there is the need to distinguish teaching the practice of
entrepreneurship (teaching it i.e. the vocational domain) from teaching about the
phenomenon (its theories) and the way it impacts on other phenomena. Fiet
(2001) argues that one way to add more theoretical content to entrepreneurship
courses is to teach students what they ought to do and why (theory). A focus on
practice and action-based learning only (non-theoretical) has limited usefulness as
a guide for instructing potential and aspiring entrepreneurs about their prospects
for future success. This is because while the context and the experiences may
Entrepreneurship Education
91
change, relationships between variables (theories) may remain relatively stable
over time. Thus, a university should teach theory first before endeavouring to
engage the students in practice. Once the theory is understood, then the practice
will have a lot more meaning (Hindle, 2007; Martin et al., 2013; Pedler, 2012;
Whitehead, 1967).
5.2.2.1.1 Curriculum, Delivery Approaches and Uptake of EE There is often a challenge when attempting to consider the quantity and quality of
EE because of diversity in curriculum (content, breadth and depth), pedagogical
approaches, and level of offering whether at post-graduate level, undergraduate
level, nascent/fledgling entrepreneur level or indeed whether it is a full programme
or merely a module/course (Blenker et al., 2011; Henry et al., 2003; Henry, 2013;
Hills, 1988; Van der Sijde, 2008). As indicated earlier, this study focuses on EE
whose purpose is to develop skills and knowledge in new venture creation
(Edelman et al., 2008), management and growth (Blenker et al., 2011; Henry et
al., 2005; Rideout and Gray, 2013).
In relation to curriculum, the Global Entrepreneurship Monitor (GEM) suggests
that there is a need to consider the nature, adequacy and level of offering of EE
(Martinez et al., 2010, p.12, p.31). In particular, EE has the objective of developing
skills and knowledge required for new venture creation, management and growth.
This is generally accepted as the dominant focus of EE (Blenker et al., 2011;
Rideout and Gray, 2013). It has its heritage from two fields. One is Schumpeter’s
(1934) and Kirzner’s (1997) neo-classical approach focusing on the entrepreneur’s
function in innovation and opportunity recognition. The other is from traditional
management theory, in which management control and planning are perceived as
the central vehicles for entrepreneurs to use to adapt to the external environment
(Arasti et al., 2012). In this vein, EE contents often come from an integration of
Entrepreneurship Education
92
marketing (Kotler, 2011; Kotler and Armstrong, 2013), strategy (Porter, 1980),
budgeting/financing and implementation analytical frameworks such as the SWOT
(strength, weaknesses, opportunities and threats) (Andrews, 1971; Johnson et al.,
2011).
Therefore, training of students in new venture creation consists of a rational
planning process which considers the relationship between an entrepreneur’s
prospective or actual new venture and its environment (Blenker et al., 2011;
Hindle, 2007; Sarasvathy, 2001). This planning and decision making process is
typically expressed in various types of models which illustrate how the potential
entrepreneur, as a decision-maker, should progress through a series of stages,
gradually gather and analyse relevant information and make rational, informed
decisions (McGee et al., 2009; Rotefoss and Kolvereid, 2005). Other scholars
suggest that besides the business planning skills, other high level entrepreneurial
capabilities in facilitating business growth, building an entrepreneurial team,
enabling intellectual property generation and commercialisation, and accessing
venture capital are also crucial (Blenker et al., 2011).
In terms of empirical research, there is a shortage of evidence as to whether
educators are actually helping students in skill and knowledge development
(Edelman et al., 2008). This observation is grounded in the notion of relevance
(Wilson and Sperber, 1992). A handful of prior studies in developed countries
attempt to establish a benchmark of entrepreneurial capabilities to be developed in
EE (Carter et al., 1996; Delmar and Shane, 2002; Gatewood et al., 1995; Rotefoss
and Kolvereid, 2005). The findings of these studies include:
Strand 1: Business Planning involving defining and identifying market
opportunities/ customers, competitors, and preparing a business plan,
Entrepreneurship Education
93
developing product/service, conducting market research, managing
(organising and controlling) start-up team, looking for and acquiring
facilities/equipment, and being devoted full time to the business;
Strand 2: Financing the new firm which involves identifying and organising
required debt and equity financing. This includes saving money to invest,
investing own money, applying for/receiving bank or government funding,
preparing and evaluating financial statements, opening and managing
relations with financial institutions for the new business; and
Strand 3: Interaction with the external environment includes formal business
registration (registering with legal authorities), applying for licences,
patents, etc., hiring and managing employees, establishing and managing
relationship with suppliers and customers, sales promotion activities,
receiving payments from sales and generating positive net income.
A study by Edelman et al (2008) compares EE curriculum obtained from educators
in USA based institutions of higher education as well as practices and capabilities
of nascent entrepreneurs. The study finds support that EE largely helps students
to develop the required start-up capabilities exhibited by nascent entrepreneurs.
However, there is a lack of evidence from developing countries (Fayolle and Liñán,
2014).
In relation to delivery approaches, scholars indicate that the link between
pedagogical approaches (Johannisson, 1991; Johannisson et al., 1998; Souitaris
et al., 2007) and outcomes of EE such as EI is unclear (Fayolle and Liñán, 2014).
In addition, prior research indicates a shortage of measures to assess the EE
delivery approaches (Rideout and Gray, 2013; Souitaris et al., 2007). Scholars
who emphasise that entrepreneurship practice and theory are interwoven often
Entrepreneurship Education
94
recommend the learning cycle introduced by Kolb (1984) as a teaching approach
in EE. According to this learning cycle, there are four connected phases (Kolb and
Kolb, 2005; Kolb, 1984; Kolb et al., 2001): i. conceptualization (learning from
theory/models/abstraction); ii. experimentation (bringing what has been learned
into practice); iii. concrete experience (doing and experiencing); and iv. reflection
(reflecting on the experience). Van der Sijde (2008) and Neck and Greene (2011)
recommend that effectiveness of EE would be dependent on the extent to which
the phases of the experential learning cycle are covered.
In line with Kolb’s learning cycle, scholars in EE generally suggest that a
combination of various pedagogical practices would be more effective in
developing entrepreneurial capabilities (Herrero and van Dorp, 2012; McMullan
and Boberg, 1991; Souitaris et al., 2007). Such approaches would include
lectures, case studies, guest entrepreneur presentations, internships/placements,
business simulations, problem-based learning and, if possible, actual venture
creation (Krueger Jr, 2007b; Krueger Jr, 2009; Mauer et al., 2009; Neck and
Greene, 2011; Stumpf et al., 1991).
In relation to the uptake of EE, how wide-spread EE is to the population should be
considered (Martinez et al., 2010, p.12, p.31). This is an indicator of how well EE
is received by different stakeholders (Matlay, 2009). The GEM special report on
EE indicates that generally innovation-driven economies have higher proportions
of the working age population trained in entrepreneurship than factor-driven and
efficiency-driven economies (Martinez et al., 2010). For instance, as indicated in
subsection 2.4.3, the average undergraduate student engagement rate in Europe
is at 23% (UK is 16%). However, for a developing country such as Zambia, the
undergraduate student engagement rate is a paltry 5%. Scholars indicate that
there is a need to generate unequivocal evidence about the effect of EE on
Entrepreneurship Education
95
entrepreneurial outcomes in order to promote the uptake of EE (Rideout and Gray,
2013). The next section (5.3) explores empirical literature on the effects of EE on
EI.
5.3 Effects of Entrepreneurship Education on Entrepreneurial Intention
Graduate entrepreneurship is concerned with the extent to which graduates as
products of university education engage in new venture creation or self-
employment (Luethje and Franke, 2004; Nabi and Holden, 2008; Nabi and Liñán,
2011). Since EE and business start-up support by government and other
stakeholders are investments toward graduate entrepreneurship, scholars
continue to call for theory grounded research to determine return on investments
(Nabi et al., 2010; Rae et al., 2012). Table 5.2 shows approaches suggested by
scholars on how to evaluate the impact of EE.
Table 5.27- Entrepreneurship Education Effectiveness Evaluation Framework
Timing of Measurement Relevant Criteria During the Entrepreneurship Education Programme (EEP)
Number of students enrolled (engagement rate)
Number and type of courses/modules
General awareness of and interest in entrepreneurship
Shortly after the EEP Intentions to act
Acquisition of knowledge, skills and inspiration
Development of entrepreneurial self-diagnosis abilities i.e. self-perception of learning and capability
Between Zero and five years after EEP
Number and type of ventures created
Number of buyouts/acquisitions
Number of entrepreneurial positions sought and obtained
Between three and ten years after EEP
Sustainability/survival and reputation of the firms
Level of innovation and capacity for change exhibited by the firms
More than ten years after the EEP
Contribution to society and the economy e.g. taxes, employment, competition, social responsibility, innovation, products/services, etc.
Business performance
Level of satisfaction with career
Source: (Block and Stumpf, 1990; Henry et al., 2004; Jack and Anderson, 1998; Jack and Anderson, 1999; Storey, 2000)
Theoretically, two perspectives suggest that EE may be positively related to
entrepreneurial intention and behavioural outcomes (Morris et al., 2013;
Vanevenhoven and Liguori, 2013). Firstly, human capital theory predicts that
Entrepreneurship Education
96
individuals who possess higher levels of knowledge, skill, and other competences
will achieve higher performance outcomes (Becker, 1962; Ployhart and Moliterno,
2011; Unger et al., 2011). There may be a positive relationship between
performance and human capital assets specific to entrepreneurship. Secondly,
based on social cognitive theory (Bandura, 1993; Chen et al., 1998; McGee et al.,
2009), entrepreneurial self-efficacy relates to the belief in one’s abilities to
successfully perform the various roles and tasks of entrepreneurship. EE is
expected to help develop entrepreneurial self-efficacy through (1) enactive
mastery – action-based learning, (2) vicarious experience - learning from case
studies and guest entrepreneurs, 3) verbal persuasion - encouragement and
theory, and (4) emotional arousal - inspiration (Hindle et al., 2009; Zhao et al.,
2005). Higher entrepreneurial self-efficacy is expected to lead to higher EI and
other entrepreneurial outcomes (Fitzsimmons and Douglas, 2011; Schlaegel and
Koenig, 2014).
There is a small but growing body of empirical research regarding the effect of EE
on EI. The nature of this body of research suggests mixed and inconsistent
conclusions10 (Bae et al., 2014; Küttim et al., 2014; Williamson et al., 2013).
Moreover, only a few studies investigate the effect of EE on EI via perceived
feasibility and desirability of entrepreneurship (Souitaris et al., 2007; Fayolle et al.,
2006; Nabi et al., 2010). On the one hand, some studies find that EE has a
positive impact on EI (Fayolle et al., 2006a; Fayolle and Gailly, 2009; Fretschner
and Weber, 2013; Gibcus et al., 2012; Sánchez, 2013; Souitaris et al., 2007).
These studies suggest that EE may cultivate a student’s attitudes and intention,
10 For a comprehensive summary of empirical studies reviewed for the period between 2002 and
2014 see Appendix 10.1
Entrepreneurship Education
97
which would ultimately lead to actual business start-up (Liñán, 2008). Martin et al.
(2013) in meta-analyses of 42 independent studies find small but statistically
significant relationships between EE and human capital outcomes, such as
entrepreneurship-related knowledge and skills (rw =0.237), a positive perception of
entrepreneurship (rw =0.109), and EI (rw =0.137). Based on longitudinal data from
undergraduate students in UK and France, Souitaris et al. (2007) find that while
entrepreneurship knowledge and skills are not significant determinants of EI,
inspiration has a significant influence on EI. In France, Fayolle and Gailly (2009)
carry out a longitudinal study of engineering undergraduate students participating
in different EE modules lasting 1 day, 3 days or 7 months. Their findings indicate
that only undergraduate students without any prior entrepreneurial exposure show
significant change in EI after the EE modules. Additionally, they find that
participants with longer EE duration have higher EI. Their results imply that
individual factors may influence the effect of EE on EI, an aspect of research that
is lacking in extant literature.
Based on longitudinal data from undergraduate students before and after EE in a
module premised on education ‘about’ entrepreneurship, Fretschner and Weber
(2013) in Germany find that EE is significantly positively associated with
desirability but not feasibility of entrepreneurship. Their conclusion is that EE
influences EI through perceived desirability but not perceived feasibility of
entrepreneurship. In a study of EE alumni and a control group for graduates of 9
universities from 9 European countries, Gibcus et al. (2012) find that EE alumni
have significantly higher positive perception of entrepreneurship, entrepreneurial
knowledge and skills although the difference in entrepreneurial self-efficacy is not
significant. EE alumni have higher proportions of self-employed individuals (16%
vs 10%) and entrepreneurs (8% vs 3%) than the control group. Among those who
Entrepreneurship Education
98
start businesses, the EE alumni start within 0.7 years of graduation while the
control group start after 2.8 years from graduation. In addition, the EE alumni
entrepreneurs have higher turnovers and innovation in their businesses than the
control group entrepreneurs.
Furthermore, the GEM conducts a cross-sectional survey of working age adults,
16-64 years old, on the effect of entrepreneurship training on entrepreneurial
outcomes from 38 countries in different phases of economic development. The
survey includes 6 factor-driven economies i.e. economies largely dependent on
primary and extractive industries (e.g. Egypt), 17 efficiency-driven economies i.e.
economies characterised by industrialisation and reliance on economies of scale
(e.g. South Africa), and 15 innovation-driven economies i.e. economies whose
industrial activity is characterised by sophistication and variety as well as intensity
in knowledge, research and development (e.g. the UK)11. The GEM findings
indicate that training increases awareness, self-efficacy and intentions but does
not influence fear of failure and capacity in opportunity recognition (Martinez et al.,
2010). Additionally, early stage entrepreneurial activity is significantly associated
with past training in entrepreneurship.
On the other hand, numerous empirical studies find that EE has either no
discernible influence or a negative influence on EI (Boissin and Emin, 2007; do
Paço et al., 2013; Marques et al., 2012; Oosterbeek et al., 2010; Packham et al.,
2010; Tegtmeir, 2012; Volery et al., 2013; von Graevenitz et al., 2010). Bae et al.
(2014) conduct meta-analyses of 73 studies and find a small but significant
association between EI and EE (r=0.143). However, Bae et al. (2014) indicate that
11 For a comprehensive discussion of differences amongst factor-, efficiency- and innovation-driven
economies please see section 2.1 in Chapter 2.
Entrepreneurship Education
99
after controlling for the pre-education intention of respondents, the post-education
intention is not significant. They recommend that future studies should focus on
various possible mediation effects and checks for self-selection bias. Based on
data from secondary school students in Portugal, Marques et al. (2012) do not find
support for any impact of EE on EI. Students who report higher EI are those who
already had prior entrepreneurial exposure. These results are not unprecedented.
Studies such as Boissin and Emin (2007) and do Paco et al. (2013) also conclude
that EE has no significant impact on EI. Volery et al. (2013) and Oosterbeek et al.
(2010) conclude that EE may even have a negative effect on EI. Based on a study
of undergraduate students in France, Germany and Poland, Packham et al. (2010)
find that EE has significant positive effect on EI for French and Polish students but
negative impact for German students. German students indicate that they are
interested in EE, not because it enables them to start a business, but because it
helps them acquire skills that improve their competitiveness when they become
employees in existing organisations. The authors speculate that low
unemployment in Germany may be a contributing factor.
The foregoing inconsistent findings have prompted scholars to suggest that since
EE and business start-up support by government and other stakeholders are
investments toward graduate entrepreneurship, further research with clear
theoretical underpinnings is required to determine return on investments (Nabi et
al., 2010; Rae et al., 2012). Additionally, scholars note that research on the
influence of EE, individual factors and contextual factors on EI has grown in
isolation from each other (Hitt et al., 2007; Shepherd, 2011; Shook et al., 2003).
Further, some scholars claim that attempts at research on contextual factors’
influence on EI have lacked sound theoretical underpinnings (Krueger, 2008; Nabi
et al., 2010). Thus, there is a shortage of studies investigating the intervening role
Entrepreneurship Education
100
of EE on the relationships between individual and contextual factors and EI (Cope,
2005; Ertuna and Gurel, 2011; Rideout and Gray, 2013).
“The real question we need to answer is: what type of EE, delivered by whom, within which type of university, is most effective for this type of student, with this kind of goal, and under these sets of circumstances (or contexts). Even at this elementary stage in its development for EE research, it is clear that if we are going to address the needs of policymakers and the constituencies and taxpayers they are responsible to, EE researchers will need to strive to answer this kind of complex question.” Rideout and Gray (2013, P.348)
Moreover, extant literature indicates a lack of research proposing and validating
integrative theory-based conceptual models in relation to determinants of EI
(Fayolle and Liñán, 2014; Krueger, 2009; Shook et al., 2003). This limits the
understanding of the interplay among various facets of EI development.
“…we need a larger pool of methodologically adequate EE research. In this regard, well-designed case studies would also be useful to help identify important mediators. We need more quantitative research that simultaneously examines the role of promising mediators like entrepreneurial self-efficacy, cognitive skills and knowledge, values and attitudes, social networks, and other contextual variables on policy relevant outcomes,…clearly there is also need for the development of psychometrically sound measures to supports these efforts.” Rideout and Gray (2013, p.348)
Lastly, the literature also shows that research on the effect of EE on EI is
predominantly conducted in developed countries, with a paucity of studies in
developing countries (Bruton et al., 2010; Hoskisson et al., 2011; Nabi and Liñán,
2011). Thus, scholars suggest that one way to build in-depth understanding of
entrepreneurial phenomena is to execute studies in diverse and under-researched
contexts (Fayolle and Liñán, 2014). This would enable stakeholders to have more
confidence that findings of research are applicable to a wider range of settings.
Entrepreneurship Education
101
5.5 Conclusions
This chapter has discussed the importance and types of entrepreneurship
education. Indeed the world is changing fast. The number of people working in
small firms or who are self-employed is growing, while employment opportunities
in large firms and the public sector are limited. Therefore, individuals seeking jobs
need to be more flexible and entrepreneurial. Enterprise education aims to
produce graduates possessing a range of essential skills and attributes to make
unique, creative and innovative contributions in the world of work.
Entrepreneurship is the application of enterprise skills specifically to creating and
growing organisations by identifying, evaluating and exploiting opportunities. The
focus of the current research is entrepreneurship education (EE) which is
concerned with the development and application of enterprising mind-sets and
skills in the specific contexts of setting up, managing and growing a venture. It is
also concerned with developing an understanding of the nature of business,
innovation and small business management and their role in economic activity.
Empirical studies on the effect of EE on EI show mixed conclusions. In light of the
foregoing inconsistent findings and knowledge gaps in the literature, the next
chapter proposes a conceptual model and develops hypotheses for investigating if
EE has an intervening role in the influence of individual and institutional factors on
EI.
102
CHAPTER 6: CONCEPTUAL MODEL AND HYPOTHESES DEVELOPMENT
6.0 Introduction
The preceding chapter reviews literature on the impact of entrepreneurship
education (EE) on entrepreneurial intention (EI). Clearly, existing literature has
mixed conclusions (Bae et al., 2014; Küttim et al., 2014); some studies report
positive impact while others show negative results. The literature also indicates a
lack of integrated conceptual models for examining the antecedents of EI (Fayolle
and Liñán, 2014; Krueger, 2009; Shook et al., 2003). In this context, this chapter
proposes a conceptual model and puts forward hypotheses in relation to EE and
EI. Specifically, this chapter includes a synthesis of theoretical background to the
proposed conceptual model (6.1); institutional factors’ influence on perceived
feasibility and desirability of entrepreneurship (6.2); individual factors’ influence on
perceived desirability and feasibility (6.3); the intervening role of EE (6.4); and, the
influence of perceived feasibility and desirability on EI (6.5).
6.1 Theoretical Background to the Conceptual Model
An established body of studies suggests that EI is central to entrepreneurship
(Bird, 1988; Krueger JR et al., 2000; Shinnar et al., 2012). EI is a self-
acknowledged conviction of a person who intends to start a business venture and
consciously plans to do so at some point in the future (Rotefoss and Kolvereid,
2005; Thompson, 2009). The literature shows that individuals with high EI are
more likely to start a business than those with low EI (Kautonen et al., 2013;
Krueger, 2008; Matlay, 2008). The GEM indicates that EI is an important measure
of potential entrepreneurship of society (Kelley et al., 2012). Thus, understanding
Conceptual Model and Hypotheses
103
EI determinants becomes important for understanding entrepreneurial behaviour
(Shane and Venkataraman, 2000).
A number of conceptual models explaining antecedents of EI (Bird, 1988; Boyd
and Vozikis, 1994; Davidsson, 1995; Krueger and Carsrud, 1993; Krueger, 1993;
Krueger and Brazeal, 1994; Lim et al., 2010; Lüthje and Franke, 2003) are
primarily based on Shapero and Sokol’s (1982) entrepreneurial event model and
Ajzen and Fishbein’s (1991, 2002, 2005) theory of reasoned action and planned
behaviour. According to these theories, EI can be parsimoniously regarded as a
function of perceived desirability and feasibility of entrepreneurship (Brännback et
al., 2006; Fitzsimmons and Douglas, 2011; Schlaegel and Koenig, 2014).
Desirability reflects the degree to which a person has a favourable evaluation of
the entrepreneurial career i.e. ‘Do I perceive that this would be a good thing for me
to do?’ Feasibility reflects an individual’s perception of ease of performing the
behaviour i.e. ‘Could I do it if I want to?’
However, extant literature raises critical questions in relation to the adequacy of
the basic EI model. Specifically, scholars indicate that there is little knowledge
about what factors determine perceptions of feasibility and desirability (Davidsson,
2004; Dohse and Walter, 2012; Hindle et al., 2009; Rideout and Gray, 2013;
Schlaegel and Koenig, 2014). In attempts to decipher the antecedents of EI,
previous research has provided two, mostly, separate strands of explanations.
Firstly, the individual-focused strand holds that individuals with personality traits,
background and demographic factors matched to entrepreneurial tasks are more
likely to have higher EI than those without (BarNir et al., 2011; Lee and Wong,
2004; Stewart Jr and Roth, 2001; Verheul et al., 2012; Zhao et al., 2010a).
Secondly, the environment-focussed strand holds that inhibiting or facilitating
factors in the external environment influence EI (Birdthistle, 2008; Luethje and
Conceptual Model and Hypotheses
104
Franke, 2004; Robertson et al., 2003; Shane, 2004; Smith and Beasley, 2011;
Walter et al., 2011). The forgoing research strands on EI have evolved relatively
isolated from each other. This view is shown in the quotes below:
“With regard to theoretical limitations, the EI literature has not resulted in cumulative knowledge because the various perspectives have been pursued in isolation from other perspectives. Future work on EI should attempt to integrate and reduce the number of alternative models.” Shook et al. (2003, p.386)
“(on the future of entrepreneurial intention research)...as Krueger (2009) suggests, the construct of intentions appears to be deeply fundamental to human decision making, and as such, it should afford us multiple fruitful opportunities to explore the connection between intent and a vast array of other theories and models that relate to decision making under risk and uncertainty. This view opens the door for the development of integrative and more sophisticated theoretical models of the entrepreneurial process… New research may consider interaction…moderation…and mediation effects.” Fayolle and Liñán (2014, p.664)
“For future research...it has become clear that an adequate theory of entrepreneurial intention should give due attention to the contextual framework in order to capture the entrepreneurial event in its various dimensions.” Dohse and Walter (2012, p.891)
As a consequence, scholars call for studies to examine how factors at the
individual and institutional levels jointly shape EI (De Clercq et al., 2011; Fayolle
and Liñán, 2014; Hitt et al., 2007; Krueger, 2009). A cross-level approach may
address inconsistent findings on determinants of EI since it may, ultimately, be
determined by a combination of dispositions, context and other interventions
(Cope, 2005; Gartner, 1989a; Hindle et al., 2009; House et al., 1996; Krueger,
2009; Mitchell et al., 2007; Wang and Chugh, 2014). In addition, the impact of
country institutional profile developed and validated in Europe and the US has not
been applied in developing countries (Bruton et al., 2010; Hoskisson et al., 2011).
Consequently, it is vital to explore whether the findings generated in the developed
economies can be replicated in the developing context (Giacomin et al., 2011).
This study aims to investigate the effect of EE on the relationships between
individual and institutional factors and EI. This proposition is based on two
Conceptual Model and Hypotheses
105
reasons. Firstly, based on reviews of extant literature, scholars indicate the need
to explore if, why and how EE and its impact may differ in different learning
contexts and with different individuals (Rideout and Gray, 2013; Wang and Hugh,
2014; Cope, 2005; Fairlie and Holleran, 2011; Liñán, 2008; Fayolle and Liñán,
2014). It would be enlightening to study EE and its interaction with contextual and
individual factors. Secondly, EI is incorporated in many studies even when
research coverage has not been extended to EE (BarNir et al., 2011; Birdthistle,
2008; Davey et al., 2011; Levenburg et al., 2006; Wu and Wu, 2008). For instance,
Luethje and Franke (2003) establish that individual factors and some elements of
the entrepreneurial environment are positively associated with EI. Therefore, it
would be worthwhile to go a step further to explore the role EE plays in this
process.
Building on Shapero and Sokol (1982) and Azjen (1991), Luethje and Franke
(2003) propose a model that examines factors influencing EI. The major
advantage of their model is that it integrates, though not comprehensively, some
elements of trait theory, contextual factors and the basic EI model to investigate
the combined effect of entrepreneurial traits, perceived barriers and support
factors on EI (Figure 6.1). However, their model neither incorporates the influence
of entrepreneurial self-efficacy (Nabi et al., 2010) nor the influence of EE on EI. In
addition, their model does not capture a wide range of institutional and individual
factors. The current research adopts and extends Luethje and Franke’s (2003)
model and attempts to investigate whether EE intervenes on the impact of
individual and institutional factors on EI. The conceptualised model is shown in
Figure 6.2 and sections 6.2 to 6.5 explain how the combined effect of these factors
influences EI.
Conceptual Model and Hypotheses
106
Figure 6.18- Luethje and Franke (2003) Entrepreneurial Intention Model
Figure 6.29- Hypothesised Model for the Mediating Role of EE
6.2 Institutional Factors’ Influence on Perceived Feasibility and Desirability
Institutional theory explains how organisational behaviour is shaped by
surrounding formal and informal institutional forces or ‘rules of the game’ (Engle et
al., 2011; Kostova, 1997; North, 1990; Scott, 1995; Scott, 2008; Szyliowicz and
Galvin, 2010). Institutional theory is widely used in sociology (DiMaggio and
Powell, 1983; Meyer and Rowan, 1977; Roy, 1997), political science (Bonchek
Conceptual Model and Hypotheses
107
and ShepSle, 1997) and economics (North, 1990). DiMaggio and Powell (1983)
classify institutions in three dimensions: coercive (legally sanctioned), normative
(morally authorised and culturally supported) and mimetic/imitative (culturally and
professionally supported way of coping with uncertainty). Following this lead,
Scott (1995) outlines three pillars: regulatory (rule-setting, monitoring, and
sanctioning activities), normative (a prescriptive, evaluative and obligatory
dimension into social life), and cognitive (shared conceptions that constitute the
nature of social reality and the frames through which meaning is constructed).
Building on Scott’s work, Kostova (1997) introduces the concept of country
institutional profile to explain how a country’s government policies (regulatory),
widely shared social knowledge (cognitive) and value systems (normative) affect
business activities. The country institutional profile reflects a country’s business
environment in an inclusive way and captures various aspects of the environment
including cultural norms (Hofstede, 1984), social knowledge, rules and regulations
(Stenholm et al., 2013). Kostova (1997) argues that institutions are context specific
and, therefore, institutional characteristics of a country should be evaluated in
relation to a specific phenomenon rather than in general.
Busenitz et al. (2000) apply the country institutional profile to explore how and why
levels of entrepreneurship vary by country. The three institutional dimensions
influence entrepreneurial attitudes, motives as well as the constraints and
opportunities for starting, managing and growing a business (Gnyawali and Fogel,
1994; Martinelli, 2004). They determine the pace and type of entrepreneurial
activity of a country (Bruton et al., 2010; Manolova et al., 2008; Spencer and
Gomez, 2004; Welter and Smallbone, 2011). Busenitz et al. (2000) further
empirically validate the country institutional profile of entrepreneurship with macro-
level data based on six developed economies, i.e. U.S., Norway, Italy, Sweden,
Conceptual Model and Hypotheses
108
Germany and Spain. Their findings indicate that the influence of the three
institutional dimensions is consistent across countries in determining rate of new
business activity. Countries where entrepreneurship is admired are more likely to
have higher start-up rates. However, it is the cognitive and regulatory dimensions
that provide the skills and necessary support for entrepreneurship. Spencer and
Gomez (2004) find that the three institutional dimensions and other economic
indicators such as GDP and unemployment determine rate of self-employment as
well as the number of small businesses and stock exchange listings. Manolova et
al. (2008), by applying the profile to three emerging economies (i.e. Bulgaria,
Hungary and Latvia), find that institutional dimensions are associated with the
GEM’s rate of entrepreneurial activity.
Institutional Factors Included and Excluded in the Model
In line with concerns by Bruton et al. (2010), Hoskkison et al. (2011) claim that
“...most research on entrepreneurship has neglected the entrepreneur’s
institutional context…not much work has been done in…contexts such as
developing economies” (p.1155). Bruton et al. (2010) argue that one major
advantage of Busenitz et al.’s (2000) framework over others is the explicit
recognition that country differences involve more than cultural values and norms.
Wicks (2001), Fayolle and Liñán (2014) and Engle et al. (2011) argue that
institutional influences should also be investigated at micro-level to determine their
impact on individual cognition and behaviour. De Clercq et al. (2011) recommend
that future studies should investigate combinations of individual and institutional
factors’ influence on perceptions of feasibility to start a business.
Therefore, Busenitz et al.’s (2000) country institutional profile for entrepreneurship
was chosen for this study because it is the only framework in the extant literature
Conceptual Model and Hypotheses
109
that effectively combines formal institutions (laws, regulations and policies), and
informal institutions (culture, values, norms and generally shared knowledge and
information in society) into one framework to assess the entrepreneurial
environment. These are the elements that scholars such as Schlaegel and Koenig
(2014) and Rideout and Gray (2013) recommend as the basis for exploring the
context-specific development of EI. Obviously this choice means that some factors
in the environment such as regional differences in start-up rates within a country,
as well as ethnic and religious diversity are not captured (Caliendo, 2013).
Regulatory Institutions’ Influence on Feasibility and Desirability
Busenitz et al. (2000) conceptualise the regulatory institution as the formal set of
laws, regulations and government policies that provide support to individuals when
they start a new venture, acquire resources and get access to markets. Engle et
al. (2011) and Gnyawali and Fogel (1994) argue that countries that offer tax
incentives and provide training and mentoring for nascent entrepreneurs are likely
to witness higher new venture creation. Favourable policies, regulations and
business support mechanisms help to reduce barriers and enhance business
capabilities (Birdthistle, 2008; Shinnar et al., 2012). For instance, scholars argue
that relaxing credit constraints allows some poor individuals to access credit for
firm formation (Bianchi, 2010). Lim et al. (2010) observe that supportive, less
complicated and less burdensome legal environment may positively influence the
rate of entrepreneurship. Favourable policies and support mechanisms also help
to promote entrepreneurship as an acceptable career path (Silva et al., 2011). This
would enhance desirability of entrepreneurship in society. Gaspar (2009) finds that
nascent entrepreneurs supported by venture capitalists and incubation services
would not decide to start if the support was not available. Others note that
Conceptual Model and Hypotheses
110
sufficient financial capital targeted at entrepreneurship increases rate of new
business activity in a country (Bowen and De Clercq, 2007).
Normative Institutions’ Influence on Feasibility and Desirability
The normative institution reflects the degree to which people in a nation admire
and value entrepreneurship as a respectable and high-status career path (Baughn
et al., 2006; Busenitz et al., 2000). While the regulatory institution tends to shape a
country's entrepreneurship in a formal way, the normative institution tends to
informally provide a shared set of practices, norms, standards and values
(Bontempo and Rivero, 1992; Frederking, 2004; Hofstede, 1984; Mueller and
Thomas, 2001; Park and Levine, 1999; Siu and Lo, 2013). Previous studies show
that a society that admires and values entrepreneurs tends to show higher interest
in entrepreneurship (Baugh et al., 2006). This type of society also encourages
more individuals to pursue entrepreneurial careers (Falck et al., 2012; Spencer
and Gomez, 2004). In Spain for instance, societal admiration of entrepreneurship
is found to have a direct impact on desirability of entrepreneurship albeit with
regional differences (Liñán et al., 2011; Liñán, 2008). From the literature, it is also
expected that the higher the societal recognition of entrepreneurship, the higher
the feasibility of entrepreneurship, since favourable normative institutions increase
the likelihood of support from peers, family and policy makers (Shapero and Sokol,
1982; Gnyawali and Fogel, 1994; BarNir et al., 2011; Verheul et al., 2012; Mauer
et al., 2009). Scholars suggest that if societal values and beliefs are favourable to
entrepreneurship, more individuals would desire to create a new venture
(Davidsson and Wiklund, 1997; Falck et al., 2012; Maria and Bygrave, 2001;
McClelland, 1961; Veciana and Urbano, 2008).
Conceptual Model and Hypotheses
111
Cognitive Institutions’ Influence on Feasibility and Desirability
The cognitive institution consists of shared knowledge and skills possessed by
people in a country pertaining to starting and operating a business (Busenitz et al.,
2000). Within countries, particular knowledge sets are institutionalised through
sharing (Busenitz and Barney, 1997; Lau and Woodman, 1995). Such knowledge
and skills would be transmitted through informal or formal general education
systems (Baughn et al., 2006; Dohse and Walter, 2012; Hindle et al., 2009;
Schenkel et al., 2009; Ucbasaran et al., 2003). De Clercq et al. (2011), Bowen and
De Clercq (2008) and Spencer and Gomez (2004) find that favourable cognitive
institutions influence rate of new business creation. Favourable cognitive institution
leads to accumulation of entrepreneurship knowledge and increases individuals’
capability in opportunity identification and exploitation (Schenkel et al., 2009;
Kirzner, 1997; Lim et al., 2010). It is expected that the greater the availability of
entrepreneurship knowledge in a society, the greater the perceived business start-
up abilities among potential entrepreneurs (Gnyawali and Fogel 1994). It is also
expected that shared information would positively affect values and beliefs about
entrepreneurship (Shapero and Sokol, 1982). Based on the above discussion, the
following hypotheses are proposed:
H1: Institutional factors are positively associated with perceived feasibility and desirability of entrepreneurship
H1a: Regulatory institution is positively associated with perceived feasibility of entrepreneurship
H1b: Regulatory institution is positively associated with perceived desirability of entrepreneurship
H1c: Normative institution is positively associated with perceived feasibility of entrepreneurship
H1d: Normative institution is positively associated with perceived desirability of entrepreneurship
H1e: Cognitive institution is positively associated with perceived feasibility of entrepreneurship
H1f: Cognitive institution is positively associated with perceived desirability of entrepreneurship
Conceptual Model and Hypotheses
112
6.3 Individual Factors’ Influence on Perceived Feasibility and Desirability
It is evident that individuals differ in ability, temperament, learning style and
socialisation (Marques et al., 2012; Nga and Shamuganathan, 2010; Obschonka
et al., 2010). Personality refers to all fundamental characteristics of a person that
endure over time and account for consistent patterns of responses to everyday
situations (Rauch and Frese, 2007). Individuals choose work environments and
jobs that match their personalities, needs and interests (Zhao and Seibert, 2006).
Facing the same opportunity, some people will decide to exploit an entrepreneurial
opportunity while others will not (Shane, 2003). Some individuals have an
entrepreneurial “career anchor” (Schein, 1996) or propensity to enterprise; a
combination of psychological traits, interacting with other contextual and
background factors, may drive them to found a business when an opportunity
arises (Gnyawali and Fogel, 1994; Marques et al., 2012; Zellweger et al., 2011).
Founding and managing a business requires that one fulfils a number of roles
such as innovator, risk taker, manager, relationship builder and goal achiever
(Chen et al., 1998). This view is widely shared in the literature (Chen et al., 1998;
Fairlie and Holleran, 2011; Zhao et al., 2010a). Studies show that individuals with
high need for achievement, internal locus of control and risk taking propensity are
more likely to engage in entrepreneurship (Fairlie and Holleran, 2011; Marques et
al., 2012; Rauch and Frese, 2007).
On the other hand, Gartner (1988) notes disappointing results of some studies that
have attempted to link individual traits to entrepreneurial behaviour (Brockhaus Sr,
1980; Brockhaus and Nord, 1979; Brockhaus and Horwitz, 1982; Sexton and Kent,
1981). Such studies find that where certain psychological traits are concerned, it
may not always be possible to distinguish entrepreneurs from the general
population. Notwithstanding the disappointing results, Dyer (1994) and Rauch and
Conceptual Model and Hypotheses
113
Frese (2007) argue that individual factors play a significant role in the selection of
an entrepreneurial career. Recent meta-analyses (Zhao et al., 2010; Rauch and
Frese, 2007) explore the influence of personality characteristics including the ‘‘Big
Five’’ (extraversion, neuroticism, agreeableness, openness to experience, and
conscientiousness) on EI. Besides observing that risk taking propensity and locus
of control are associated with entrepreneurship, researchers find that openness to
experience, conscientiousness, and extraversion lead to EI and entrepreneurial
success (Obschonka et al., 2010; Zhao et al., 2005). Frank et al. (2007) further
find that the influence of personality traits is more significant at the venture
creation stage, but less significant at the venture survival and growth stages. At
the venture survival and growth stages, skills, the environment and resources are
more significant.
Individual Factors Included and Excluded in the Model
This study chooses to include four individual factors, namely risk taking propensity
(RTP), internal locus of control (ILC), need for achievement (NAch) as well as prior
entrepreneurial exposure (PEE). The rationale for this choice is two-fold. Firstly, as
discussed in section 6.1, Luethje and Franke’s (2003) model, which is employed
as a foundation for the current research, uses RTP and ILC to represent individual
characteristics. The current study not only adopts RTP and ILC from Luethje and
Franke’s (2003) model but also includes NAch because the three personality traits
are the most consistent and common characteristics reflected in prior research
(Zhao et al., 2010; Thomas and Mueller; 2001; Fairlie and Holleran, 2011; Rauch
and Fese, 2007; Luethje and Franke, 2003). Secondly, the study also includes
prior entrepreneurial exposure because scholars indicate that it is the common
background factor associated with entrepreneurship (Zellweger et al., 2011;
Krueger, 1993; BarNir et al., 2011). Prior research shows that individuals are
Conceptual Model and Hypotheses
114
morely likely to have an understanding of what is involved in entrepreneurship, if
they i) started and managed a business previously; ii) have a parent/family
member who has started and managed a business; iii) work in family business; or
iv) closely work with an entrepreneur.
Obviously the choice of the four individual factors implies that other factors are
excluded such as psychological characteristics of desire for independence,
disagreeableness, extraversion, over-confidence, representativeness and
intuitiveness (all these have been discussed in section 3. 3). In relation to an
individual’s background, factors such as family wealth, social ties and networks, as
well as friends’ and family’s advice and support in the choice of career and study
programmes, are excluded (Ride and Gray, 2013; Caliendo, 2013; Clarke, 2005).
While the excluded individual factors may have an influence on EI (Falck et al.,
2012; Rauch and Frese, 2007), they are not among the common and consistent
determinants of EI in prior research (Frank et al.,2007; BarNir et al., 2011; Thomas
and Mueller, 2001).
Risk Taking Propensity’s Influence on Feasibility and Desirability
The most studied personality characteristic in the context of entrepreneurship is
risk taking propensity (Fairlie and Holleran, 2011). RTP entails willingness to
pursue opportunities and courses of action involving uncertainty (Zhao et al.,
2010). Early scholars indicate that an individual willing to bear risk is more likely to
choose to be an entrepreneur (Cantillon, 1755; Cole, 1942; Knight, 1921; Mill,
1848). Contemporary scholars continue to view proclivity to take risks as a pre-
requisite for engaging in entrepreneurship (Frank et al., 2007; Hermann, 2011;
Rauch and Frese, 2007). Others consider RTP as the hallmark of the
entrepreneurial personality (Begley and Boyd, 1986). Empirical findings show that
Conceptual Model and Hypotheses
115
moderate and high risk takers are more likely to be entrepreneurs (Rauch and
Frese, 2000; Rauch and Frese, 2007; Stewart, 1996) and that the RTP of
entrepreneurs is generally higher than that of non-entrepreneurs (Stewart and
Roth, 2001). Before a new product or service is introduced, an individual cannot
know with certainty that he/she can produce desired outputs (technical risk), meet
consumers’ needs (market risk), generate profits in competition (competitive risk)
and be able to repay debt (financial risk). In fact, the future cannot be known with
certainty (Knight, 1921; Wu, 1989).
Some individuals, more than others, would be eager to start something new or
engage in an activity even if they have no guarantee. Individuals with high RTP
are generally open minded and feel capable of dealing and coping with uncertainty
and risk. Such individuals are expected to be excited about starting a business.
Besides being attracted to start the new business, such individuals are expected to
have high perceived capability of handling and coping with the uncertainties. Prior
studies indicate that individuals with high RTP are more likely to choose an
entrepreneurial career (Segal et al., 2005; Verheul et al., 2012; Zhao et al., 2005).
This is because such individuals would consider business start-up not only
possible but also worthwhile.
Internal Locus of Control’s Influence on Feasibility and Desirability
Studies in psychology reveal that individuals with higher ILC have higher self-
esteem, self-efficacy and emotional stability (Judge et al., 2002). An individual with
higher ILC believes that he or she can influence any outcomes through capability
and effort. On the other hand, an individual with lower ILC believes that factors
beyond one’s personal control determine outcomes (Rotter, 1966). Recent findings
confirm that people with stronger ILC are more adept at dealing with the pressures
Conceptual Model and Hypotheses
116
at work and can cope with change more effectively (Frank et al., 2007). Not
surprisingly, ILC is one of the most studied psychological traits in entrepreneurship
(Thomas and Mueller, 2001; Rauch and Frese, 2007). Since individuals with high
ILC believe in their own abilities to achieve outcomes and give little credence to
external forces and barriers, they are more likely to regard entrepreneurship
attractive and possible (Rotter, 1966). This is because such individuals like to be
initiators, taking responsibility for their own welfare and are independent from
others; entrepreneurship offers them such an opportunity (McClelland, 1961).
Individuals with high ILC are more likely to start a business for two major reasons.
Firstly, individuals with high ILC find activities that provide a direct link between
effort and outcomes attractive (Thomas and Mueller, 2001; Frank et al., 2007).
Business start-up provides a direct link between effort and outcomes. Despite the
challenges involved, an entrepreneur’s efforts would eventually be rewarded
through the survival and growth of the business along with the other benefits of
these achievements. Therefore, it is expected that individuals with high ILC will
find business start-up attractive. This would be reflected in high desirability of
entrepreneurship. Secondly, individuals with higher ILC would also feel more
capable of handling the pressures and the uncertainties of business start-up than
individuals with low ILC (Frank et al., 2007). This is because such individuals
generally have a higher degree of belief in their abilities and effort to influence
outcomes in any activity. Additionally, such individuals believe they can achieve
their goals despite external forces and barriers.
In support of these perspectives, literature indicates that there are at least some
general agreements that the entrepreneur, however defined, is a self-motivated
individual who takes the initiative to start and build an enterprise relying primarily
on self rather than others to formulate and implement his or her goals (Shapero,
Conceptual Model and Hypotheses
117
1975; Krueger and Brazeal, 1994; Thomas and Mueller, 2001). Other scholars find
that an individual’s belief that capability and effort will determine outcomes is
crucial to the new venture creation decision (Brockhaus and Horwitz, 1982; Frank
et al., 2007; Lee and Tsang, 2001; Lüthje and Franke, 2003; Rauch and Frese,
2007; Verheul et al., 2012). Thus, individuals with high ILC would engage in
entrepreneurship because such individuals are more likely to find business start-
up both attractive and possible.
Need for Achievement’s Influence on Feasibility and Desirability
Need for achievement is among the most researched personality characteristics
associated with entrepreneurship (Rauch and Frese, 2007; Frank et al., 2007). In
fact, scholars indicate that it is the most consistent personality predictor of job
performance across all types of work and occupations (Zhao and Seibert, 2006).
NAch is an individual’s persistence, hard work and motivation for significant
accomplishment (McClelland, 1961; McClelland, 1965; McClelland, 1967). A high
NAch is a motivation that leads an individual to seek activities and tasks that
demand individual effort and skill, and provide clear feedback on outcomes.
Because entrepreneurship requires significant effort, persistence and skill,
individuals with high NAch are more likely to fit in. Except for a few studies that
indicate otherwise (Cromie, 2000; Littunen, 2000), most empirical research finds
that individuals who have a higher NAch are more likely to be entrepreneurs
(Collins et al., 2004a; Dohse and Walter, 2012; Frank et al., 2007; Kristiansen and
Indarti, 2004; Rauch and Frese, 2007; Volery et al., 2013). This is because NAch
drives individuals to seek careers and tasks in which performance is due to one’s
own efforts and not the efforts of others.
Conceptual Model and Hypotheses
118
Prior Entrepreneurial Exposure’s Influence on Feasibility and Desirability
In addition to the foregoing major individual characteristics, extant literature
indicates that an individual’s background influences the likelihood of business
start-up (Dyer, 1994; Zellweger et al., 2011). Shapero and Sokol (1982) and
Krueger (1993) indicate that one of the major factors associated with
entrepreneurship is prior entrepreneurial exposure (PEE). Scholars indicate that
individuals with PEE are more likely to find entrepreneurship attractive. They are
also more likely to have confidence in their abilities to start and manage a
business. This is because such individuals are exposed to entrepreneurship; they
have some levels of understanding of what is involved in entrepreneurship. With a
few exceptions, such as Zhang et al. (2013), scholars find that individuals who
have a) a parent/family member who is an entrepreneur, b) started a business
before, or c) worked closely with an entrepreneur, are more likely to start a
business (Falck et al., 2012; Verheul et al., 2012; Krueger, 1993). Based on the
above perspectives on individual factors, the following hypotheses are proposed:
H2: Individual factors are positively associated with perceived feasibility and desirability of entrepreneurship H2a: Risk taking propensity is positively associated with perceived feasibility of
entrepreneurship H2b: Risk taking propensity is positively associated with perceived desirability of
entrepreneurship H2c: Internal locus of control is positively associated with perceived feasibility of
entrepreneurship H2d: Internal locus of control is positively associated with perceived desirability of
entrepreneurship H2e: Need for achievement is positively associated with perceived feasibility of
entrepreneurship H2f: Need for achievement is positively associated with perceived desirability of
entrepreneurship H2g: Prior entrepreneurial exposure is positively associated with perceived feasibility of
entrepreneurship H2h: Prior entrepreneurial exposure is positively associated with perceived desirability of
entrepreneurship
Conceptual Model and Hypotheses
119
6.4 Intervening Role of Entrepreneurship Education
Whether or not entrepreneurship can be taught is an area of on-going debate
(Aronsson, 2004; Gendron et al., 2004; Kuratko, 2003; Solomon, 2007). However,
many scholars agree that attitudes, behaviour, and mind-set associated with
entrepreneurship can be developed or enhanced through education and training
(Baron and Ensley, 2006; DeTienne and Chandler, 2004; Hindle, 2007; Klein and
Bullock, 2006; Ucbasaran et al., 2008; Williamson et al., 2013). Specifically,
individuals can learn approaches for generating and evaluating business ideas,
ways to identify and serve markets, strategies to adopt for market entry as well as
acquisition and management of resources (Bosma et al., 2004; Davidsson and
Honig, 2003; Shepherd and DeTienne, 2005).
Various pedagogical practices can be used to develop entrepreneurial self-
efficacy. Such approaches include lectures, case studies, guest entrepreneur
presentations, internships/placements, business simulations as well as problem-
based learning (Krueger Jr, 2007b; Krueger Jr, 2009; Mauer et al., 2009; Neck and
Greene, 2011; Stumpf et al., 1991). Knowledge about the benefits of
entrepreneurship to individuals and society may help portray entrepreneurship as
a legitimate, socially respectable and desirable career path (Walter et al., 2011).
This may encourage students to pursue entrepreneurial careers (Kolvereid, 1996b;
Peterman and Kennedy, 2003).
There is a shortage of studies exploring whether EE has an intervening role on the
influence of institutional and individual determinants of EI (Liñán and Fayolle,
2014). Based on Shapero and Sokol (1982), Ajzen (1991) and Franke and Luthje
(2003), the current research builds a case for the possible intervening role of EE
from two angles. Firstly, extant literature indicates that positive perception of the
business environment influences new business creation (Zahra, 1993; Zahra and
Conceptual Model and Hypotheses
120
Covin, 1995; Souitaris et al., 2007). It is expected that favourable institutional
factors promote entrepreneurship by a) enhancing the perception that it is
achievable because of low barriers, and b) enabling people to realise its
importance and value. Therefore, favourable institutions would also positively
influence people’s interest in EE, whilst interest in EE will affect the level of
entrepreneurship knowledge and skills acquired through EE i.e. effectiveness of
EE (Lewis et al., 2009; Potvin and Hasni, 2014). Effective learning from the EE will
further enhance the understanding of the benefits of entrepreneurship (Mauer et
al., 2009; Fayolle et al., 2006; Souitaris et al., 2007). Thus, effectiveness of EE
would in turn influence the perception that business start-up is not only worthwhile
but also possible.
Secondly, while EE clarifies the benefits and develops knowledge and skills about
entrepreneurship, individuals differ in ability, temperament, personality, interests,
and socialisation. Some factors on which individuals differ determine whether one
considers the tasks, roles, and activities of entrepreneurship attractive and
possible (Shane, 2003; Frank et al, 2007). Individuals with characteristics required
for entrepreneurship would have favourable attitudes towards entrepreneurship
and, therefore, prefer EE. This favourable predisposition is expected to affect
performance and effort in EE, ultimately influencing the effectiveness of EE i.e. the
level of knowledge and skills acquired through EE. Effectiveness of EE would in
turn influence perceived feasibility and desirability of entrepreneurship. These
perspectives resonate with suggestions by scholars that personal interests
determine choices and intensity when engaging in any aspect of education,
potentially influencing its impact (Lewis et al., 2009; Matlay, 2010). Thus scholars
indicate that attitude/interest/motivation affect performance, and perception of
such in education (Potvin and Hasni, 2014). Based on this rationale, the detailed
Conceptual Model and Hypotheses
121
proposed mediating12 influences of EE are discussed in subsections 6.4.1 and
6.4.2.
6.4.1 Entrepreneurship Education Mediating the Influence of Institutions
Regulatory Institution and Effectiveness of Entrepreneurship Education
The regulatory institution comprises laws, regulations and government policies
that provide support and administrative procedures facilitating business start-up
(Busenitz et al., 2000). Would-be entrepreneurs are likely to consider themselves
capable of launching businesses if they perceive that the entrepreneurial
environment is supportive (Chen et al., 1998; Mauer et al., 2009; Shapero and
Sokol, 1982). This is because favourable regulatory institutions not only reduce
perceived start-up barriers but also promote entrepreneurship by signalling that
this is important to society. It is further proposed that favourable regulatory
institutions also promote entrepreneurship by affecting the population’s interest
and attitude toward entrepreneurship and EE. This interest and the resulting effort
in EE will affect the rate and level of entrepreneurship knowledge and skills
acquired i.e. effectiveness of EE. Effectiveness of EE will in turn affect the thinking
that business start-up is possible and worthwhile. Extant literature on general
education indicates that attitude toward a subject influences effort and the
consequent performance (Blickle, 1996; Chamorro‐Premuzic and Furnham, 2003;
De Fruyt and Mervielde, 1996; Lewis et al., 2009; Lievens et al., 2002).
12 Choice of mediation analysis, rather than moderation, was based on guidelines by Baron and Kenny (1986,
p1174): that it is desirable that the moderator variable be uncorrelated with both the predictor and the dependent variable to provide a clearly interpretable interaction term. Another property of the moderator variable is that, unlike the mediator-predictor relation (where the predictor is causally antecedent to the mediator), moderators and predictors are at the same level in regard to their role as causal variables antecedent or exogenous to certain criterion effects. That is, moderator variables always function as independent variables, whereas mediating events shift roles from effects to causes, depending on the focus of the analysis.
Conceptual Model and Hypotheses
122
Entrepreneurship skills and knowledge acquired through EE are expected to
enhance one’s human capital by increasing a) opportunity recognition abilities (Lim
et al., 2010; Robison and Sexton 1994; Arenius and DeClercq 2005) and b)
opportunity exploitation capabilities (Martínez et al., 2010; Oosterbeek et al., 2010;
Souitaris et al., 2007; von Graevenitz et al., 2010). Thus, the regulatory institution
would influence perceived feasibility and desirability of entrepreneurship indirectly
via effectiveness of EE.
Normative Institution and Effectiveness of Entrepreneurship Education
The normative institution reflects the degree to which society admires and
values entrepreneurship, creativity and innovation (Busenitz et al., 2000). The
higher entrepreneurship is positioned in an economy, the more favourable the
citizens’ attitude toward entrepreneurship (Baughn et al., 2006; Davidsson, 1995;
Thomas and Mueller 2001; Kennedy and Peterman, 2003; Walter et al., 2011) and
the higher the likelihood that individuals obtain support at the start-up stage
(Shapero and Sokol 1982; BarNir et al., 2011; Mauer et al., 2009). Societal
admiration of entrepreneurship would not only affect the attitude and interest
toward business start-up but also attitude toward EE. Since societal admiration of
entrepreneurship would affect individuals’ attitudes to EE, it means that the
favourable normative institution would affect effort, zeal as well as actual and
perceived performance in EE (Lewis et al., 2009). This would be reflected in the
effectiveness of EE. Effectiveness of EE is the level of knowledge and skills
acquired through EE (Liñán, 2008). EE is expected not only to develop
entrepreneurial capabilities and skills but also enhance understanding of the
benefits and importance of entrepreneurship (Mauer et al., 2009; Zhao et al.,
2005; Fayolle and Gailly, 2006; Krueger, 2007; Neck and Greene, 2011).
Therefore, effectiveness of EE would in turn influence the thinking that business
Conceptual Model and Hypotheses
123
start-up is not only desirable but also feasible. Based on these perspectives, it is
expected that relevant normative institutions would influence perceived feasibility
and desirability via effectiveness of EE.
Cognitive Institution and Effectiveness of Entrepreneurship Education
The cognitive institution reflects the shared knowledge and skills, possessed by
people in a country, pertaining to establishing and operating a new business
(Busenitz et al., 2000). Availability of business knowledge increases perceived
abilities for new venture creation among would-be entrepreneurs (Gnyawali and
Fogel, 1994). In addition, shared entrepreneurship knowledge promotes
entrepreneurship in society (Shapero and Sokol, 1982). It is expected that
favourable cognitive institutions would affect not only the population’s attitude to
entrepreneurship but also the attitude to EE. Since individuals’ attitude affects
learning efforts, receptiveness and performance (Lewis et al., 2009), it is expected
that the level of knowledge and skills acquired through EE would be influenced by
cognitive institutions. EE not only promotes entrepreneurship through knowledge
about its importance and benefits (Walter et al., 2011; Matlay, 2008; Bowen and
De Clercq, 2007) but also enhances individuals’ human capital through improving
their abilities in opportunity recognition and exploitation (Arenius and Clercq, 2005;
Lim et al., 2010; Oosterbeek et al., 2010; von Graevenitz et al., 2010). This would
increase individuals’ likelihood of starting a business (Davidsson and Honig, 2003;
Delmar and Davidsson, 2000; Robinson and Sexton, 1994). Therefore, relevant
cognitive institutions would influence perceived feasibility and desirability of
entrepreneurship indirectly via effectiveness of EE. In line with the above
perspectives on how relevant institutions may influence effectiveness of EE, it is
postulated as follows:
Conceptual Model and Hypotheses
124
H3: Entrepreneurship education mediates the effects of institutional factors on perceived feasibility and desirability of entrepreneurship H3a: Entrepreneurship education mediates the effect of regulatory institution on perceived
feasibility and desirability of entrepreneurship H3b: Entrepreneurship education mediates the effect of normative institution on perceived
feasibility and desirability of entrepreneurship H3c: Entrepreneurship education mediates the effect of cognitive institution on perceived
feasibility and desirability of entrepreneurship
6.4.2 Entrepreneurship Education Mediating the Influence of Individual
Factors
Risk Taking Propensity and Effectiveness of Entrepreneurship Education
Risk taking propensity reflects an individual’s willingness and readiness to
pursue opportunities and courses of action involving uncertainty (Zhao et al.,
2010). Bearing and managing risk is a fundamental aspect of entrepreneurship.
Individuals with high RTP are more likely to regard business start-up as desirable
and viable (Zhao et al., 2005; Frank et al., 2007; Segal et al.,2005; Luethje and
Franke, 2003; Verheurl et al., 2012; Rauch and Frese, 2007). This is because
such individuals are generally comfortable dealing with uncertainty and risky
situations. As Individuals with high RTP are more likely to have a favourable
attitude to entrepreneurship, they are more likely to be receptive to learn about
entrepreneurship. Consequently, the difference in interest and effort would affect
performance in EE i.e. effectiveness of EE. Extant literature on general education
indicates that attitude influences learning effort and the consequent performance
(Blickle, 1996; Chamorro‐Premuzic and Furnham, 2003; De Fruyt and Mervielde,
1996; Lewis et al., 2009; Lievens et al., 2002). Effectiveness of EE refers to the
level of knowledge and skills acquired through EE. Through various pedagogical
approaches, EE helps develop entrepreneurial knowledge and skills as well as an
understanding of the benefits of entrepreneurship (Fayolle et al., 2006; Nabi et al.,
Conceptual Model and Hypotheses
125
2010; Souitaris et al 2007; Matlay, 2008). Thus, effectiveness of EE would
influence the perception that business start-up is not only worthwhile but also
viable. Based on these considerations, it is expected that RTP would exert its
influence on perceived feasibility and desirability indirectly via effectiveness of EE.
Internal Locus of Control and Effectiveness of Entrepreneurship Education
An individual with an internal locus of control believes that through effort one
can achieve his or her goals (Ahmed, 1985; Rotter, 1966). Individuals with high
ILC are more likely to choose an entrepreneurial career (Rauch and Frese, 2007;
Frank et al., 2007; Verheul et al., 2012; Luethje and Franke, 2003). This is
because such individuals find entrepreneurship attractive as it provides a direct
link between effort and outcomes. Furthermore, individuals with higher ILC would
generally enter EE with higher confidence in their ability to perform in education
and in the challenging tasks of entrepreneurship. Such individuals would be
learning to perform tasks that they already find challenging and attractive. Hence,
they would be more eager to learn how to be successful entrepreneurs. Extant
literature on general education indicates that attitude influences effort in learning
and the consequent performance (Blickle, 1996; Chamorro‐Premuzic and
Furnham, 2003; De Fruyt and Mervielde, 1996; Lewis et al., 2009; Lievens et al.,
2002). The high interest in entrepreneurship by individuals with high ILC would
affect effort and, hence, performance in EE i.e. effectiveness of EE. Effectiveness
of EE refers to the level of entrepreneurship knowledge and skills acquired through
EE. Through various pedagogical approaches, EE develops entrepreneurial skills
and knowledge as well as an understanding of the benefits entrepreneurship (Von
Graevenitz et al. 2010; Mauer et al., 2009; Marques et al., 2012). Thus, EE would
influence the perception that entrepreneurship is valuable and possible. The
Conceptual Model and Hypotheses
126
current research posits that ILC would exert its influence on perceived feasibility
and desirability indirectly via effectiveness of EE.
Need for Achievement and Effectiveness of Entrepreneurship Education
Need for achievement is an individual’s persistence, hard work and motivation for
significant accomplishment (McClelland, 1961; McClelland, 1965; McClelland,
1967). A high NAch is a motivation that leads an individual to seek activities and
tasks that provide clear feedback on outcomes; activities that pose a high
challenge and yet achievable through individual effort and skill. Starting and
managing one’s own business is one such activity. Since individuals with high
NAch are likely to find entrepreneurship attractive (Rauch and Frese, 2007; Dohse
and Walter, 2012), such individuals are also likely to have high interest in EE. This
would affect effort and the consequent performance in EE (Lewis et al., 2009;
Matlay, 2010). EE develops one’s entrepreneurial capabilities and clarifies the
benefits of entrepreneurship (Gibcus et al., 2012; Morris et al., 2013). This would
in turn influence confidence that business start-up is achievable and valuable.
Based on these considerations, it is expected that NAch would exert its influence
on perceived feasibility and desirability indirectly via effectiveness of EE.
Prior Entrepreneurial Exposure and Effectiveness of Entrepreneurship Education
Scholars indicate that individuals with high prior entrepreneurial exposure (PEE)
are more likely to find entrepreneurship attractive (Falck et al., 2012). They are
also more likely to have confidence in their abilities to start and manage a
business (Krueger, 1993; Zellweger et al., 2011). This is because such individuals
are exposed to entrepreneurship; they have some level of understanding of what
is involved in entrepreneurship and its benefits. Because of their interests in
entrepreneurship, such individuals are expected to have high interest in EE
(Peterman and Kennedy, 2003). This would affect effort and the consequent
Conceptual Model and Hypotheses
127
performance in EE (Lewis et al., 2009; Matlay, 2010). EE clarifies the rewards of
entrepreneurship and develops one’s entrepreneurial capabilities (Gibcus et al.,
2012; Morris et al., 2013). This would in turn influence confidence that business
start-up is possible and valuable. Based on these considerations, it is expected
that PEE would exert its influence on perceived feasibility and desirability indirectly
via effectiveness of EE. On the basis of the above perspectives, the following
hypotheses are proposed:
H4: Entrepreneurship education mediates the effects of individual factors on perceived feasibility and desirability of entrepreneurship H4a: Entrepreneurship education mediates the effect of risk taking propensity on
perceived feasibility and desirability of entrepreneurship H4b: Entrepreneurship education mediates the effect of internal locus of control on
perceived feasibility and desirability of entrepreneurship H4c: Entrepreneurship education mediates the effect of need for achievement on
perceived feasibility and desirability of entrepreneurship H4d: Entrepreneurship education mediates the effect of prior entrepreneurial exposure on
perceived feasibility and desirability of entrepreneurship
6.5 Influence of Perceived Feasibility and Desirability on EI
An individual’s intention determines whether a particular course of action is
pursued or not (Bird, 1988; Gasse and Tremblay, 2011). It reflects a person’s
beliefs and willingness to engage in certain behaviour (Fishbein and Ajzen, 2011).
Since one’s intention is a good predictor of subsequent behaviour (Ajzen, 2011b;
Henley, 2007; Kautonen et al., 2013), understanding the nature of the immediate
antecedents of EI is of crucial importance to the study of entrepreneurial behaviour
(Shane and Venkataraman, 2000). Some scholars propose that entrepreneurial
motivation is largely based on “pull” factors (Gilad and Levine, 1986). This means
that individuals seeking independence, self-fulfilment, wealth, and other desirable
outcomes are more likely to find entrepreneurship attractive (Keeble et al., 1992;
Orhan and Scott, 2001). This is because such Individuals may believe that
entrepreneurship, compared to other alternatives, offers better means for
Conceptual Model and Hypotheses
128
achieving these desirable outcomes (Carter et al., 2003; Segal et al., 2005;
Shapero and Sokol, 1982). Therefore, they would choose an entrepreneurial
career.
Similarly, Vroom’s expectancy theory (Vroom, 1964) suggests that an individual
will choose to engage in a particular behaviour if a) he or she believes that the
outcome of those actions is attractive (i.e. valence or value) and b) he/she expects
that those actions will be followed by a given outcome (i.e. expectancy). Scholars
suggest that the concepts of valence and expectancy are the same as desirability
and feasibility, respectively (Steel and Konig, 2006). Therefore, consistent with
the basic EI model (Shapero and Sokol, 1982; Ajzen, 1991; Bandura, 2002), it can
be argued that an individual’s preferences and choice of which behaviour to
actively pursue will be dependent on the evaluative criteria of desirability and
feasibility for that behaviour (Gollwitzer, 1996; Steel and König, 2006; Veciana et
al., 2005). Perceived desirability of entrepreneurship refers to the personal
attractiveness of entrepreneurship. It is expected that individuals who find the
rewards of starting and managing their own business attractive would not only find
entrepreneurship valuable but they would also choose an entrepreneurial career.
Similarly, perceived feasibility of entrepreneurship is the degree to which one
believes that not only is he/she personally capable of starting and managing a
business but that entrepreneurship is a viable undertaking. It is expected that
individuals who consider themselves personally capable of starting and managing
a business would choose an entrepreneurial career. Prior studies provide
evidence that the consistent immediate antecedents of EI are perceived feasibility
and desirability of entrepreneurship (Brännback et al., 2006; Krueger JR et al.,
2000; Li, 2007; Liñán and Chen, 2009; Schlaegel and Koenig, 2014). For instance,
Fitzsimmons and Douglas (2011) establish that the higher the level of perceived
Conceptual Model and Hypotheses
129
feasibility and desirability of entrepreneurship, the higher the level of EI. On the
bases of the above evidence, it is hypothesised as follows:
H5: Perceived feasibility and desirability of entrepreneurship are positively associated with entrepreneurial intention
H5a: Perceived desirability of entrepreneurship is positively associated with entrepreneurial intention
H5b: Perceived feasibility of entrepreneurship is positively associated with entrepreneurial intention
6.6 Conclusions
EI is critical in the entrepreneurial process because individuals with high EI are
more likely to start a business than those with low EI. The small but growing body
of research on the impact of EE on EI shows mixed and sometimes contradictory
conclusions. Some studies find positive effect and others report negative impact of
EE on EI. Responding to this knowledge gap, this chapter proposes a conceptual
model and develops hypotheses to guide enquiry into whether EE has an
intervening role on the relationships between individual and institutional factors
and EI. Specifically, the chapter hypothesises that individual and institutional
factors exert their influence on perceived feasibility and desirability of
entrepreneurship in two ways: directly and indirectly via effectiveness of EE.
Perceived feasibility and desirability of entrepreneurship in turn determine EI. To
test the model and develop in-depth understanding of the phenomena, both
qualitative research and quantitative research are required. The next chapter
emphasises the justification for the adopted concurrent triangulation strategy,
sampling and data collection procedures as well as validity and reliability of
measurements.
130
CHAPTER 7: RESEARCH DESIGN, METHODS AND TECHNIQUES
7.0 Introduction
The preceding chapter develops the conceptual model of the study. This chapter is
concerned with the research methodology. In the extant literature, the majority of
studies investigating the effect of entrepreneurship education (EE) on
entrepreneurial intention (EI) employ quantitative strategies (Rideout and Gray,
2013) and they are conducted in developed countries, therefore limit
generalisability of findings elsewhere (Gartner, 2010; Nabi and Liñán, 2011;
Solesvik et al., 2013). Combinations of positivistic research (addressing ‘what’
issues) and interpretivistic research (addressing ‘why’ and ‘how’ issues) are rare
and yet important for model testing and in-depth understanding of research
problems (Gartner, 2010; Stevenson and Jarillo, 1990; van Burg and Romme,
2014). This chapter includes six sections: justifications for research design choice
and implementation (7.1); population, sampling and data collection procedures
(7.2); validity and reliability analyses of quantitative research measures (7.3, 7.4
and 7.5); and statistical controls as well as checks for common methods bias (7.6).
7.1 Research Design Choice, Justifications and Implementation
Scholars portray research design as the overall plan for undertaking research and
it comprises an intersection of philosophies, approaches, strategies and related
methods of enquiry (Creswell, 2009; Creswell, 2014). The central point is that it is
a framework for the generation of evidence that is suitable for examining research
questions (Bryman and Bell, 2011; Denzin and Lincoln, 2011). In this regard,
research design explicitly or implicitly involves decisions about research
philosophy, which in turn guides the research approach chosen. Research
Research Design and Implementation
131
approach influences selection of strategy of inquiry which in turn has a bearing on
choice of research methods. Research methods are simply a collection of
techniques and procedures for collecting and analysing data (Gill and Johnson,
2002; Saunders et al., 2012). Figure 7.1 depicts these interrelationships.
Figure 7.110 – Saunders et al.’s (2012) Research Design Elements
7.1.1 Research Philosophy
Research philosophy involves a set of assumptions/beliefs about how the world
operates. This set of beliefs places strict guidelines and principles on how
research should be conducted (Burns and Burns, 2008). Consequently, it is an
overarching term that refers to how new knowledge is developed in a particular
field and what the nature of that knowledge is (Saunders et al., 2009). Not only
does it reflect the relationship between knowledge and the process of generating
it, but also it is the basis for choice of particular research approach, strategy and
methods. In social sciences, philosophy has four constituent elements:
epistemology, axiology, ontology and the nature of human action/behaviour
(Bryman and Bell, 2011; Gill and Johnson, 2002; McAuley et al., 2007). Firstly,
Research Design and Implementation
132
epistemology focuses on whether knowledge can, is or should be generated
objectively or subjectively. Secondly, axiology considers judgements of value that
guide choice among various alternative steps in the process of social enquiry
(Heron, 1996). Thirdly, ontology considers the nature of knowledge and
phenomena as to whether they exist objectively or subjectively. Fourthly,
assumptions about the nature of human behaviour focus on how the ontological
difference between social phenomena and objects of investigation in natural
sciences should be taken into account when conducting research (Bryman and
Bell, 2011; McAuley et al., 2007; Schutz, 1962; Schutz, 1970).
Any research philosophy adopted reflects an intersection of epistemological,
ontological, axiological and nature of human action considerations (Creswell,
2014; Crotty, 1998; Denzin et al., 2008; Guba, 1990; Guba and Lincoln, 1994;
Kuhn, 1970; Lincoln and Guba, 2000; Mertens, 2009; Neuman, 2009). Despite
several variations of the terminology, broadly there are four research philosophies
i.e. positivism, interpretivism, realism and pragmatism (Saunders et al., 2009).
Each of these is briefly discussed below:
7.1.1.1 Positivism Positivism, originating from “positive philosophy” coined by the 19th century French
philosopher August Compte (Compte, 1854; Compte, 1975), largely adopts natural
scientists’ stance of ‘working with observable social reality’. The end product of
such research can be law-like generalisations similar to those produced by natural
scientists (Remenyi et al., 1998). Positivism seeks to explain what happens in the
social world by searching for causal relationships between its constituent parts
(Burrell and Morgan, 1979). This entails employing and extending existing theory
to develop hypotheses. The hypotheses developed become the basis for fact
gathering (observable reality) that provides the basis for subsequent testing. The
Research Design and Implementation
133
end result is confirmation, in whole or in part, or rejection of the hypotheses (Gill
and Johnson, 2002; McAuley et al., 2007; Popper, 1959; Popper et al., 1972).
Positivism also embraces highly structured, systematic and objective methods
(nomothetic methods) in order to facilitate research replication and generalisability
of findings (Baker, 2003; Burrell and Morgan, 1979; Gill and Johnson, 2002). The
emphasis is quantifiable observations that lend themselves to statistical analyses
(Bryman and Bell, 2011; Burrell and Morgan, 1979; Remenyi, 1998).
The main critique against positivism is its lack of recognition that there is an
ontological difference between social phenomena and the objects of investigation
in natural sciences. Unlike natural sciences, social sciences focus on human
action which has an internal logic of its own. This internal logic should be explored
in order to understand why an individual behaves the way he or she does (Gill and
Johnson, 2002; Laing, 1967). This latter perspective is the basis for the research
philosophy that is discussed next.
7.1.1.2 Interpretivism Interpretivism fully recognises the ontological difference between social
phenomena and the research objects in natural sciences. Consequently, it
encourages social scientists to grasp the subjective meaning of social action
(Bryman and Bell, 2011; Weber, 1947). The challenge for research is to adopt an
empathetic stance i.e. to enter the social world of the research subjects and
understand the scenario from their point of view (Saunders et al., 2009). The
following quote from Schultz offers the core of this philosophy (Schutz, 1962;
Schutz, 1970):
“The world of nature as explored by the natural scientist does not “mean” anything to molecules, atoms and electrons (it-beings). But the observational field (context) of the social scientist – the social reality- has specific meaning and relevance structure for the human beings living, thinking and acting within it. By a series of common-sense constructs, they
Research Design and Implementation
134
have pre-selected and pre-interpreted this world which they experience as the reality of their daily lives. It is these thought objects of theirs which determine their behaviour by motivating it. The thought objects constructed by the social scientist, in order to grasp this social reality, have to be founded upon the thought objects constructed by the common-sense of men and women living their daily lives within the social world.” (Schutz 1962, p. 59, quoted in Bryman and Bell, 2011).
The central theme of interpretivism is that individuals’ interpretation, meaning and
understanding of the world around them (i.e. social context) form the basis for their
actions (Blumer, 1966; Blumer, 1986; Bryman and Bell, 2011; Dewey, 1931;
Mead, 1925; Mead, 2009; Rose, 1962). Interpretivism further holds that not only
are social situations complex but they are also unique; they are a function of a
particular set of circumstances and individuals involved (Bogdan and Taylor, 1975;
Bryman and Bell, 2011). The implication is that research that aims to capture the
rich complexity of social situations is unlikely to generate findings which are
generalisable to the larger population. The social world is ever changing;
circumstances of today may not repeat in future and each social setting is
different. Hence, interpretivism leads to adopting a flexible research process and
methods which flow from the views gathered from the subjects of research.
Indeed, interpretivism embraces methods that capture subjective accounts
generated by getting inside research subjects’ situations to understand their point
of view (ideographic methods).
7.1.1.3 Realism Realism holds that there is reality whose existence is independent of people’s
knowledge and description of it. Thus, social scientists should direct their attention
to examine and understand this reality (Bhaskar, 2008; Bryman and Bell, 2011;
Johnston and Smith, 2010; Saunders et al., 2009). Realism shares two features
with positivism. Firstly, both paradigms suggest that the natural and social
sciences can and should apply the same kinds of approach and methods for
collection, analyses, understanding and explanation of data (Bryman and Bell,
Research Design and Implementation
135
2011). Secondly, both paradigms suggest that there is an external and objective
reality to which scientists should direct their attention. In other words, there is
reality that is separate or independent from researchers (Saunders et al., 2009).
There are two major forms of realism that are often contrasted. Firstly, empirical
realism simply asserts that through use of appropriate methods, reality can be
understood. Because it focuses on observable reality, it “fails to recognise that
there are enduring structures and generative mechanisms underlying and
producing observable phenomena and is, therefore, superficial” (Bhaskar,1978,
p.2). Secondly, critical realism (CR) is a specific form of realism whose manifesto
is to recognise the reality of the natural order, events and discourses of the social
world. However, CR goes further to recognise that, “we will only be able to
understand- and so change- the social world if we identify the (unobservable)
structures at work that generate those (observable) events and discourses….
These structures are not spontaneously apparent in the observable pattern of
events; they can only be identified through the practical and theoretical work of the
social scientists” (Bhaskar, 1975, p.150, quoted in Bryman and Bell, 2011, p.17).
As a result, the proper job of scientists is to attempt systematically to identify the
entities responsible for an event and to describe the generative mechanism
(Bhaskar, 1978a; Bhaskar, 1978b; Bhaskar, 1998; Bhaskar, 2008; Johnston and
Smith, 2010).
7.1.1.4 Pragmatism Pragmatism is a philosophical tradition with the view that sometimes choosing one
philosophical paradigm (e.g. positivism) rather than the other (e.g. interpretivism)
may be unrealistic in practice. Consequently, pragmatism suggests that the most
important determinant of choice of research philosophy is the nature of the
research question(s). On the one hand, one philosophical paradigm may
sometimes be more appropriate than the other(s) to answer particular research
Research Design and Implementation
136
questions(s). On the other hand, if the nature of the research question does not
suggest unambiguously that either a positivist or an interpretivist philosophy be
adopted, this suggests the pragmatist’s view may be a possibility. This view
derives from the work of Peirce, James, Mead and Dewey (Cherryholmes, 1992;
Creswell, 2014; Saunders et al., 2009) and other recent writers (Murphy and
Rorty, 1990; Patton, 1990; Patton, 2005; Rorty, 1990). Pragmatism is generally
concerned with what is applicable (i.e. what works) to find a solution for a research
problem (Patton, 1990). The main point is that researchers should focus on the
research problem and then use all relevant and necessary research paradigms,
approaches and methods to comprehensively understand the research problem
(Creswell, 2014; Patton, 1990; Patton, 2005; Rossman and Wilson, 1985). As a
consequence, pragmatism is usually the philosophical underpinning for mixed
research strategies and methods (Morgan, 2007; Saunders et al., 2009;
Tashakkori and Teddlie, 1998; Tashakkori and Teddlie, 2010).
7.1.1.5 Justification for the Philosophical Choice Based on the nature of the research problem, pragmatism was chosen as the
research paradigm underpinning this study. Firstly, research investigating the
effect of EE on EI has yielded equivocal conclusions. Secondly, there is a
shortage of research examining the possibility that EE intervenes in the
relationships between EI and its individual and institutional determinants. Further,
only with a few exceptions (Matlay, 2008; Woodier-Harris, 2010), most studies on
EI are not only positivistic (Gartner, 2010; Rae, 2000) but they are also conducted
in developed countries, limiting the generalisability of prior research findings
elsewhere (Nabi and Liñán, 2011). Consequently, scholars call for research on EI
that use multi-methods to address challenges in prior research (Fayolle and Liñán,
2014).
Research Design and Implementation
137
With this background, both quantitative research and qualitative research were
required. With regard to model testing, it was planned to employ the positivistic
paradigm. This was because highly structured and objective methods were able to
assess whether the conceptual model could be accepted and generalised to the
relevant population. However, positivistic research has its limitations.
“With quantitative (positivistic) research, we cannot capture the decision dynamics that underlie the hypothesised relationships—that is, the individual cognitive processes by which the macro-level factors we study affect and complement people’s resources in their decision to engage in new business activity (Lim et al., 2010). Additional research might use qualitative interviews with entrepreneurs, as well as other stakeholders involved in entrepreneurship support or policy making, to capture and measure individual-level cognitive mechanisms that facilitate, or hamper, the full exploitation of their and others’ resources to support new business endeavours.” De Clercq et al. (2011, p.17)
Qualitative research based on the interpretivistic paradigm was required for in-
depth understanding of the research problem from the Zambian context (Blundel,
2007; Bygrave, 1989; Gartner, 2010; Rae, 2000). The overall rationale was that
triangulation would provide the basis for determining convergence or divergence of
findings on the social phenomenon.
7.1.2 Research Approaches and Theory
Research approach is the process by which social science theories are generated,
evaluated and justified (Gill and Johnson, 2002; Saunders et al., 2009).
Consequently, it is a general orientation of the relationship between theory and
research (Bryman and Bell, 2011, p11). Generally, there are two major
approaches to research: induction (for theory building) and deduction (for theory
testing).The two alternatives should not be seen as mutually exclusive; in many
cases, they can complement each other (Blundel, 2007; Danermark, 2002;
Eriksson and Lindström, 1997; Gill and Johnson, 2002; Lawson, 1996; Lewin and
Research Design and Implementation
138
Cartwright, 1952; Patokorpi, 2006; Peirce, 1955; Saunders et al., 2009). Induction
and deduction are explained below.
7.1.2.1 Inductive Approach If research follows a sequence that starts with specific observations (data),
followed by description and analysis of data to determine if there are patterns
emerging as a basis for explaining what is observed (theory), the approach is said
to be inductive. It is a bottom-up approach which develops theory from initial data
(Burns and Burns, 2008; Bryman and Bell, 2011). In this sense, induction starts
from the specific (observations) and proceeds to the general (theory). Inductive
inference means drawing general conclusions based on a limited number of
observations. It is assumed that what is valid for the observed cases may also be
valid for the whole population in that context (Bryman and Bell, 2011; Hempel and
Oppenheim, 1948). Since inference is not dependent on any premises, the
discovery of new knowledge is unlimited. However, the weakness of induction is
that it is difficult to say for sure to what extent the findings can be generalised
because of limitations in sample size.
7.1.2.2 Deductive Approach Unlike the inductive approach, the deductive approach reverses the sequence of
the research process. It starts with using existing theory, developing hypotheses,
collecting and analysing data (observations) in order to test, refute or confirm the
hypotheses (Burns and Burns, 2008; Saunders et al., 2009). Thus, the deductive
approach is a top-down process working from the general (theory) to the specific
(observation). Deductive inference means using formal logic to deduce
conclusions from given premises (Bryman and Bell, 2011; Popper, 1959). The
strength of deductive inference is that it tells researchers whether their conclusions
are valid or not. The weakness, however, is that deductive approach may not be
Research Design and Implementation
139
able to provide the in-depth rationale for human behaviour i.e. it may be not able to
adequately answer the how and why questions of social phenomena.
7.1.2.3 Justification for Research Approach Generally, deduction is associated more with positivism and induction with
interpretivism. However, some scholars argue that this classification is potentially
misleading and of no real practical value (Lund, 2005; Saunders et al., 2009).
Moreover, pragmatic perspectives suggest that it is possible for a research cycle
to emerge where conclusions of an inductive approach (theory building) can be
further evaluated to confirm the findings using the deductive approach (theory
testing). Conversely, it is also possible that a deductive study may unearth some
unexpected and hard to explain result which could then be explored by using an
inductive approach (Burns and Burns, 2008; Lund, 2005; Creswell, 2014).
Creswell (2014) suggests criteria to determine whether a particular research
problem should be tackled inductively or deductively or both. Firstly, a topic in
which there is a lot of literature from which one can define a theoretical framework
and hypotheses lends itself more to deduction. However, for topics that are new
and on which there is scant literature, it may be more appropriate to work
inductively by generating data, analysing it, and reflecting on the theoretical
themes the data suggests. Secondly, the time available may also be an issue.
Deductive research can be quicker while inductive research can be more
protracted. Lastly, the needs, interests, preferences and practicalities for
stakeholders should be another guide for the decisions (Buchanan et al., 1986;
Buchanan and Bryman, 2009; Saunders et al., 2009). For the current research,
after conceptualising a model based on extant literature, a deductive quantitative
approach was necessary for model tesing. At the same time, since the Zambian
Research Design and Implementation
140
context is under–researched, it was necesssary to have an in-depth understanding
of the research issues.
7.1.3 Research Strategies
Research strategy is a general orientation to the conduct of research and it can
either be a qualitative or quantitative strategy or both (Bryman and Bell, 2011).
While some argue that qualitative/quantitative research classification is
ambiguous, not useful or even false (Layder and Layder, 1993), others insist that
the classification is very informative (Saunders et al., 2009). Any strategy chosen
provides specific direction for the methods and techniques to be used in data
collection and analyses (Saunders et al., 2009; Creswell, 2014). Alternative
research strategies are briefly explained below.
7.1.3.1 Quantitative and Qualitative Strategies Quantitative research strategy emphasises quantification (numbers) in the
measurement, collection and analysis of empirical data. This may require a
deductive approach where the focus is theory testing (Saunders et al., 2009). This
strategy not only incorporates the practices and norms of the natural scientific
model but also embodies a view of social reality as an external, objective reality.
Conversely, qualitative research is a strategy that emphasises narrative
experiences and accounts of social actors rather than quantification of empirical
data. This predominantly relies on an inductive approach where the focus is on
theory generation/building. This strategy rejects the practices and norms of the
natural scientific model. Instead, the strategy emphasises on the ways in which
individuals interpret their social world. This strategy embodies a view of social
reality as a constantly shifting emergent property of individuals’ creation (Bryman
and Bell, 2011). Thus, it stresses the importance of understanding social
Research Design and Implementation
141
phenomena through gathering subjective viewpoints or meaning held by relevant
individuals.
7.1.3.2 Mixed Methods Strategies Mixed methods strategies originated in the 1950s’ when scholars utilised multi-
methods to validate psychological traits (Campbell and Fiske, 1959; Creswell,
2014). The recognition that qualitative and quantitative methods should be viewed
as complementary rather than rival led to the preference for mixed methods, given
the strengths and weaknesses inherent in each single method (Denzin, 1970;
Denzin, 1978; Denzin and Lincoln, 2011; Jick, 1979; Tashakkori and Teddlie,
2010; Webb et al., 1966). Mixed methods strategies can be employed for
illustration, convergent validation or the development of analytic density or
‘‘richness’’ (Fielding and Fielding, 2008; Fielding, 2010; Fielding and Fielding,
1986; Fielding, 2012). Triangulation is about examining a research issue from
different angles (Denzin, 1970). While triangulation is initially understood as a
validation strategy, broadly, four different forms are available:
a) Data triangulation: gathering and comparing different types of data from
different sources e.g. data about the same phenomenon from different
stakeholder groups may be collected at different times and social situations;
b) Investigator triangulation: the use of more than one researcher to gather
and interpret data so as to balance out the subjective influences of
individuals;
c) Theoretical triangulation: the use of more than one theoretical position in
interpreting data; and,
d) Methodological triangulation: the use of more than one method for data
collection.
Research Design and Implementation
142
Broadly, there are two uses of methodological triangulation. Firstly, triangulation
can be the combination of two different methodologies in a study of research
objects. As Webb et al. (1966) argued, once a proposition has been confirmed by
two or more independent processes, the uncertainty of its interpretation is greatly
reduced. Convergence or agreement between two methods enhances
researchers’ belief that the results are valid (Bouchard, 1976). However, if results
between two methods are divergent, this raises additional research issues to be
investigated. This kind of triangulation is labelled by Denzin (1978, p.302) as
"between-methods" triangulation.
Secondly, another use of methodological triangulation is "within-method” (Denzin,
1978). This entails use of multiple techniques within a given method to collect and
interpret data. For instance, for quantitative methods such as survey, this can take
the form of using multiple scales about the same variable. For qualitative methods
such as participant observation, this may entail observing multiple groups whose
results can be compared. This helps the researcher to develop more confidence in
the emergent theory (Glaser and Strauss, 2009). In short, "within-method"
triangulation essentially involves cross-checking for internal consistency or
reliability while "between-methods" triangulation tests the degree of external
validity.
To implement “between-methods” triangulation, Creswell (2009, 2014) proposes
three basic alternative strategies:
Concurrent Triangulation Strategy This strategy involves collecting both qualitative and quantitative data
concurrently and then comparing the results to determine if there is
convergence or difference. This comparison is also known as confirmation,
disconfirmation, cross validation, or corroboration (Creswell, 2014; Morgan,
Research Design and Implementation
143
2007). The overall purpose is to provide comprehensive analyses of the
research problem by comparing integrated information during the
interpretation of the overall results.
Explanatory Sequential Triangulation Strategy This strategy is characterised by the feature that the collection and
analyses of quantitative data (phase 1) informs the collection and analyses
of qualitative data (phase 2). Phase 2 builds on the initial results of phase 1
and its purpose is to provide a follow up in-depth explanation and
interpretation of specific, especially unexpected, quantitative results (Morse,
1991). The challenge with this strategy is the choice of specific results to
further explore and the unequal sample sizes for each phase.
Exploratory Sequential Triangulation Strategy This strategy involves qualitative data collection and analyses at phase 1,
followed by quantitative data collection and analyses at phase 2. The
primary purpose of this strategy is to explore a phenomenon, then
quantitatively test elements of an emergent theory resulting from the
qualitative phase in order that qualitative findings can be generalised
(Morgan 2007; Morse 1991). This strategy can also use qualitative results
to develop, build or identify an instrument that best fits the context under
study (Creswell and Clark, 2007). Of particular challenge with this strategy
is sample selection for both phases as well as the qualitative findings to
focus on as a basis for the quantitative research (Creswell and Plano-Clark,
2011; Creswell, 2014).
Research Design and Implementation
144
7.1.4 Justification for Research Strategy and Methods
The research strategy chosen for this study was concurrent triangulation; this
meant collecting both quantitative and qualitative data simultaneously. The
strategy was intended for model testing and in-depth understanding of phenomena
(Creswell, 2014; Morse, 1991). The basis for this choice was three-fold. Firstly,
because there was existing literature from which a conceptual model and
hypotheses could be developed, a quantitative study was deemed appropriate for
model testing. The quantitative research ensured that highly structured and
objective methods were employed in order to test hypotheses, facilitate research
replication and generalise findings. This was accomplished through the survey
method, facilitated by a structured self-completed questionnaire as a data
collection instrument (Appendix 7.5). This method is the most common in EI and
EE research (Liñán et al., 2011; Souitaris et al., 2007; Fayolle et al., 2006). But
this method was not adequate to comprehensively address the problem given the
fact that previous studies on the effect of EE on EI have yielded mixed
conclusions. Scholars indicate that quantitative research can only identify
relationships between variables but cannot provide in-depth rationale (Gartner,
2010; De Clercq et al., 2011). For in-depth rationale, qualitative research is
required.
“…at the methodological level…following suggestions by Shook et al. (2003), researchers in EI should attempt to triangulate their findings using multi-method studies.” Fayolle and Liñán (2014, p.664)
“…only a few studies in entrepreneurship employ mixed methods strategies. Mixed methods may help to improve entrepreneurship research addressing challenges emphasised in earlier studies…to advance our understanding of the entrepreneurial phenomena.” Molina-Azorin et al. (2014, p.425)
“…qualitative phenomenon-driven research…is especially effective in addressing “how” and “why” in unexplored or underexplored research areas with little viable theory and empirical evidence.” Wang and Chugh, (2014, p.41)
Research Design and Implementation
145
Secondly, due to the foregoing limitations of quantitative research, qualitative
research was required to provide in-depth understanding of the research issues
from the under-researched Zambian context (Creswell, 2014; Morse, 1991). To
facilitate qualitative research, insights based on the knowledge and experiences of
relevant stakeholder groups were sought through in-depth interviews, as a
research method. The interviews were facilitated by a semi-structured
questionnaire as a data collection instrument (Appendix 7.4). One advantage of
interviews is the likelihood of collecting affluent information, as well as allowing the
interviewer to clarify any responses. However, one disadvantage is the limited
number of interviews one can have due to various resource constraints
(Colombotos, 1969; Creswell, 2014; Novick, 2008; Opdenakker, 2006). Qualitative
research has not been intensively used by studies investigating the effect of EE on
EI.
Lastly, it was believed that through the concurrent triangulation strategy, the
combined research results may provide a deeper and broader understanding of
entrepreneurial intention and the associated factors (Fielding and Fielding, 2008;
Fielding, 2012; Stevenson and Jarillo, 1990; van Burg and Romme, 2014). Figure
7.2 below summarises the research procedure.
Research Design and Implementation
146
Figure 7.211- Framework of the Research and Methodology
Detailed Literature Review (Chapters 3,4,5,6)
Detailed review of existing literature on
Individual and institutional factors’ effects on entrepreneurial intention (EI)
Effect of entrepreneurship education (EE) on EI
Development of conceptual model hypothesising the intervening role of EE on the relationships between EI and its determinants
Research Methodology
(Chapter 7)
Sample for the qualitative study
3 Practitioners from government and non-government entrepreneurship support institutions
3 Educators – EE university lecturers
7 final year undergraduate students participating in EE
Research Methodology (Chapter 7)
Sample for the quantitative study
Undergraduate students across disciplines in private and public universities (student population:40,000, final year students: 10,000 with 500 participating in EE)
Actual sample -1000 self-completion questionnaires
administered, yielding 878 responses (452 EE
participants and 426 non-EE participants)
Qualitative Research
(Chapter 8)
13 in-depth semi-structured interviews to
Provide in-depth understanding of the conceptual model from the Zambian context
Quantitative Research
(Chapter 9)
Utilising factor, reliability, correlation, regression and statistical mediation analyses to
Purify the measurement constructs
Test hypotheses regarding the effect of EE on the relationships between EI and its individual and institutional determinants
Model Development (Chapter 6,8,9)
Developing and validating the model through
Literature review on EI models and knowledge gaps
(Shapero and Sokol, 1982; Ajzen, 1991; Luethje and Franke, 2003; Schlaegel and Koenig, 2014; Fayolle et al., 2006; Souitaris et al., 2007; Rideout and Gray, 2013; Fayolle and Liñán, 2014; Bae et al., 2014;
Busenitz et al., 2000; Bruton et al., 2010; Wicks, 2001)
Qualitative and Quantitative findings from this research Conclusions, Limitations and
Future Directions (Chapter 10)
Introduction and Context (Chapters 1, 2)
Introduction, research context and justification
Research Design and Implementation
147
7.2 Population and Samples
The principal purpose of this study was to investigate the effect of EE on the
relationships between individual and institutional factors and EI of university
graduates. As discussed in Chapter 2 (section 2.3), Zambia is experiencing a
problem of high youth and graduate unemployment and there is need to explore
determinants of EI in order to understand how to promote graduate
entrepreneurship. This would benefit the society because prior research in
developed countries indicates that graduates, especially EE alumni, are more
likely to engage in entrepreneurship at a high level (Gibcus et al., 2012; Pickernell
et al., 2011). However, in the absence of a database of contact details for
graduates who had previously received EE, university students, particularly final
year students were the proxy population.
Using final year students as a target research population is an acceptable method
to examine EI (Kolvereid, 1996; Krueger, 1993; Krueger et al., 2000; Luethje and
Franke, 2003; Souitaris et al., 2007; Liñán et al., 2011; Iavlokeva et al., 2011; Nabi
et al., 2010). This is because firstly, final year students face an immediate career
choice and starting a business may be a realistic option for some (Segal et al.,
2005; Krueger et al., 2000). Thus, they may answer the research questions more
consciously (Bateman and Zeithaml, 1989; Trice, 1991). In addition, their
responses are more likely to be predictive of actual career choices (Liñán and
Chen, 2009; BarNir et al., 2011). Secondly, final year students face what Shapero
and Sokol (1982) refer to as a displacement event. This means an event that
prompts an individual to consider doing or not doing something. In this case,
completion of their undergraduate studies compels them to consider the best
available opportunity. Their alternatives typically include organisational
employment, starting a business or embarking on further studies. Thirdly, prior
Research Design and Implementation
148
studies find that individuals, including graduates, in the age group 22 to 35 years
exhibit the highest propensity to start-up a business if enabling factors are in
place. Indeed final year students fall in this category (Henley, 2007; Liñán, 2008;
Reynolds et al., 2002).
Research Sample Selection
For the qualitative study, a purposive sample of 7 final year undergraduate
students undertaking EE was selected. Additionally, 3 practitioners from
entrepreneurship support institutions and 3 entrepreneurship educators (university
lecturers) were included. This is because it was believed that practitioners and
educators would provide a more comprehensive assessment of the
entrepreneurial environment and the factors influencing EI.
For the quantitative study, while the total student population in Zambia was about
40000, around 10 000 were final year students. Due to budgetary, time and
logistical constraints, it was impractical to collect data from all final year university
students. Therefore sampling from final year students was undertaken. There were
12 established universities in Zambia at the time of the survey (i.e. those that had
been in existence for more than 5 years); 3 public and 9 private universities. While
about two thirds of the student population were in public universities, only one third
were in private universities. From the estimated number of final year students of
10,000, only 500 participated in EE (UNESCO Institute of Statistics, 2013;
Southern African Regional Universities Association, 2012; Universities in Zambia,
2013). At the time of data collection, only 8 of the 12 universities had students
available for the survey. Students in the other 4 universities were on holiday.
However, none of the universities whose students were on holiday offered EE.
Research Design and Implementation
149
With a population of 10,000, the minimum required representative sample size
would be 370, at confidence level of 95% and margin of error of 5%13 (Saunders et
al., 2009, p.212 and p.585). To reduce the likelihood of low reponse rate, 1000
questionnaires were delivered and this yielded an actual sample of 878. This
represented a response rate of 87.8%, exceeding the minimum 370 required for a
representative sample. The survey sample selection procedure is shown in Table
7.1a.
Table 7.1a – Survey Sample Selection Procedure
# Description Number
1 Total Undergraduate Student Population 40,000
2 Final Year Students (Target Research Population) 10,000
3 Final Year Students Not Participating in Entrepreneurship Education (EE)
9500
4 Final Year Students Participating In EE 500
5 Required Representative Sample From Target Population (Assuming 100% Response Rate)
370
6 Survey Questionnaires Administered (To Mitigate Risk of Low Response Rate) i.e. 500 EE Participants and 500 Non-Participants
1000
7 Useful Completed Questionnaires Received (actual Sample)
878
8 Proportion Of Non-Participants In EE in the Actual Sample
426/878=49%
9 Proportion Of EE Participants In the Actual Sample 452/878=51%
13
𝒏 =𝑵(𝒑% 𝑿 𝒒% 𝑿 𝒛𝟐)
(𝑵 − 𝟏)𝒆%𝟐 + (𝒑%𝑿𝒒%𝑿𝒛𝟐)
Where
n is the minimum sample size required (see also http://www.raosoft.com/samplesize.html,) N is the population size ρ% is the proportion belonging to a specified category (if unknown use 50% which gives the largest sample size) q% is the proportion not belonging to the specified category z is the z value corresponding to the level of confidence(Z= 1.96 for 95%, 2.57 for 99%, 1.65 for 90% ) e% is the margin of error that can be tolerated ( usually 5%, 1% or 10% in line with Confidence level)
Research Design and Implementation
150
Internal and External Validity in Qualitative and Quantitative Research With the concurrent triangulation strategy adopted for this research, both internal
and external validity were checked. LeCompte and Goetz (1982) suggest that
internal validity considers whether there is a good match between the researcher’s
observations (data) and the theoretical ideas they develop. Internal validity is a
particular strength of qualitative research because transcripts of interviews,
especially if they are confirmed by the participants, provide a basis for checking
the level of congruence between concepts and observations. External validity
refers to the degree to which the findings can be generalised across a social
setting (Guba and Lincoln, 1994; LeCompte and Goetz, 1982; Lincoln and Guba,
1985; Lincoln and Guba, 1986). Lecompte and Goetz (1982) argue that, unlike
internal validity, external validity presents a problem in qualitative research
because of the tendency to employ small samples. In this study, the sample for the
qualitaive research represented a diverse range of stakeholders in the social
setting. A sample of 13 participants still presents an external validity problem
(Cook, 2008). However, this problem is addressed through the quantitative study
which had a large sample for the survey (878). Therefore, the current study
achieves internal validity through qualitative research and external validity through
quantitative research.
7.2.1 Qualitative Study: Sample, Data Collection and Demographic Profile
After designing the semi-structured interview questionnaire based on the literature
review and the conceptual model, the instrument was piloted with research active
experts for content validity. The questionnaire was revised based on comments
from these specialists. This was necessary to ensure that the questions were clear
and appropriate to address the research objectives. The interviews were
conducted from February 2013 to April 2013. A non-probability purposive sample
of 13 participants ensured a mix representing the key stakeholder groups. The
Research Design and Implementation
151
profiles of interview participants are shown in Table 7.1b and explained in the
subsequent paragraphs.
Table 7.1b8- Profiles of Interview Participants
Profiles of Practitioners Three practitioners from entrepreneurship support institutions were interviewed. At
the time, there were three major public institutions supporting and facilitating
entrepreneurial activities in Zambia. Representatives from two of these institutions
participated in the interviews. Institution D was a public institution established to:
a) provide low interest finance to small and medium-sized enterprises (SMEs); and
b) promote initiatives such as skills development, preferential procurement, joint
ventures between Zambians and foreign investors. The manager interviewed had
worked in the institution for over 7 years. Institution E was also a public institution
and offered a range of services to promote SMEs. Its services included linking
nascent entrepreneurs to key institutions that would facilitate their start-up
processes, access to finance, SME support incentives and market linkages. The
manager interviewed had worked in this sector for over 15 years. Institution F
was a non-profit entity providing enterprise support based on funding from
international donor agencies. The support normally targeted specific sectors and
vulnerable groups such as youths and fledgling cooperatives in rural areas. The
entity had been operational for 15 years and the manager interviewed had worked
in the sector for over 5 years.
Age Gender Participant Affiliation/ Organisation Qualifications/ Degree enrolled
26 Female Student Private University A BA Business Administration
34 Male Student Public University B BCom Entrepreneurship
33 Female Student Public University B BCom Entrepreneurship
24 Male Student Public University C BA Business Administration
25 Male Student Public University C BA Business Administration
22 Female Student Public University C Bsc Agro Forestry
32 Male Student Public University C BSc Wood Science and Technology
50 Male Lecturer Private University A BA and MBA
37 Male Lecturer Public University B Bsc and MBA
58 Male Senior Lecturer Public university C BA, MBA, PhD
32 Female Practitioner - Regional Manager Public Support Institution D BSc and MBA
46 Male Practitioner - Director Public Support Institution E MA/MBA
40 Female Practitioner - Regional Manager Non-Profit Support Institution F BBA, Dip. Acc
Research Design and Implementation
152
Profiles of Entrepreneurship Educators University A was a private university with 10 years of existence. At the time of
interviews, it had been offering entrepreneurship modules to its final year business
degree students for more than 3 years. The lecturer interviewed had been involved
in EE since the beginning. University B was a public university with 8 years’
history. It had been providing EE for more than 4 years. The university offered two
introductory modules, one in each of the two semesters to all its first year
students. During the final two years of study, the university also offered
entrepreneurship modules as electives for business and agriculture students.
Furthermore, this university offered a bachelor’s degree in entrepreneurship and
the first cohort graduated in 2013. The lecturer interviewed had been involved in
EE since inception. University C was a public university which had 25 years’
history. This university offered EE as electives or compulsory modules to final year
students registered for degrees in business and agriculture. The lecturer
interviewed had been involved in EE for at least 10 years. For all the three
universities represented, EE delivery involved lectures, practical assignments and
projects as well as events facilitating interaction with entrepreneurs and enterprise
support institutions. Only university B offered EE related internships.
Qualitative Data collection and Analyses Procedure
At the start of each interview, the objectives of the study were stated;
confidentiality and ethical issues were explained and cleared. The interview
conversations were recorded with the permission from interviewees. After
transcribing the interviews, each participant was asked to read through her or his
transcript to confirm the accuracy. Once respondent validation was obtained,
Nvivo was used to analyse the data. The coding approach in analysing the data
Research Design and Implementation
153
was based on two considerations: i) the themes identified in the literature review
based conceptual model; and, ii) new themes suggested by the interview data.
7.2.2 Quantitative Study: Sample, Data Collection and Demographic Profile
Based on the literature, and in some cases with consent from the authors, some
constructs for the survey were adopted from previous studies. After designing the
structured survey questionnaire, the instrument was piloted with research active
experts for content validity. Thus, the questionnaire was revised based on
comments from these specialists. This was necessary to ensure that the questions
were clear and appropriate to address the research objectives. The survey was
undertaken from February 2013 to April 2013 towards the end of the academic
year for the universities concerned. The questionnaire was administered during
lectures in classrooms. Classroom completion of questionnaires is a practical
approach often used by many researchers relying on student samples in the EI
studies (Andrew C., 2007; Autio et al., 2001; Prieto et al., 2010; Wu and Wu,
2008). In addition, this approach has often been used in EE research (Packham et
al., 2010; Oosterbeek et al., 2010; Iakovleva et al., 2011). From the extant
literature, the approach normally generates a high response rate of more than
60%.
Actual Data Collection and Demographics of the Sample To gain access to final year undergraduate students in Zambia, contacts were
made with the Vice Chancellors’ offices (see Appendix 7.3). Since the number of
final year students participating in EE was only 500, the primary focus of data
collection was to distribute the questionnaires to all the 500 EE participants. Then
the next thing was to administer the questionnaire to students not participating in
EE for purposes of comparative analyses.
Research Design and Implementation
154
With the help of officials coordinating class timetables, final year classes (lessons)
were identified. The questionnaire was disseminated to the respondents in their
classes i.e. every student attending class received a questionnaire. The
respondents were required to complete the questionnaires and return them to the
researcher upon completion without discussing with classmates. This approach
minimised not only the likelihood of answering to please the researcher but also
the pressure to answer in a manner that is socially desirable (Dillman, 2000;
Saunders et al., 2009). In addition, for those final year students not participating in
EE, all accessible classes with more than one discipline such as marketing,
computer science, agriculture, social work, law, electrical and mechanical
engineering were included. Including all available students made the sample a
better representation of the population. With this approach, the actual sample
generated was 878; 426 EE non-participants and 452 EE participants i.e. 90.4% of
EE participants were included. Table 7.2 provides the comprehensive profile of
the sample.
Research Design and Implementation
155
Table 7.29- Profile of the Sample of Final Year University Students
Table 7.2 reports the distribution of the sample by type of university; 44.7% private
and 55.2% public. The actual student proportions in the population with respect to
type of university were 40.0% private and 60.0% public (SARUA, 2012). A chi-
square goodness-of-fit test indicated that there was no significant difference
between the sample (55.2%) and population (60.0%) proportions i.e. χ2(1, n=878)
=1.125, p<0.079. This distribution would allow for findings to be generalised to
private and public universities.
As indicated in Table 7.2, 44.3% of the respondents were female while 55.7%
were male. This pattern of females being fewer than the males was also reflected
in the population of university students with 39% females and 61% males
(SARUA, 2012). A chi-square goodness-of-fit test indicated that there was no
significant difference between the sample (55.7%) and population (61%)
Entrepreneurship Education All Respondents (N=878)
PROFILE ELEMENT Participants Non-Participants
n (%) n (%) n (%)
Gender Female 205 45.4 184 43.2 389 44.3
Male 247 54.6 242 56.8 489 55.7
Age 25 years and below 276 65.2 295 71.8 571 68.5
26-30 years 70 16.5 69 16.8 139 16.7
31-35 years 27 6.4 15 3.6 42 5.0
36 years and above 50 11.8 32 7.8 82 9.8
University Type Private 201 46.5 178 43.0 379 44.7
Public 231 53.5 236 57.0 467 55.2
Field of Study Non Business degree 191 44.4 220 55.3 411 46.8
Business degree 239 55.6 193 46.7 432 49.2
Discipline Business 239 55.6 193 46.7 432 51.2
Engineering, Applied Sciences, ICT & Built Environment 24 5.6 134 32.4 158 18.2
Natural Resources and Agriculture 90 20.9 10 2.4 100 11.9
Social Sciences 77 17.9 76 18.4 153 18.1
Employment None 278 65.6 314 77.0 592 71.2
Experience below 2 years 85 20.0 59 14.5 144 17.3
2- 6 years 45 10.6 27 6.6 72 8.7
6- 10 years 11 2.6 6 1.5 17 2.0
above 10 years 5 1.2 2 0.5 7 0.8
Entrepreneurial Role Model
Parent/family NO 197 44.0 216 53.0 393 47.0
YES 235 56.0 188 47.0 443 53.0
Research Design and Implementation
156
proportion for males i.e. χ2(1, n=876) = 1.086, p <0.099. This distribution allowed
for generalisability of the findings and meaningful comparison between genders.
With regard to age, 85.2% of the respondents were 30 years old and below. The
Table 7.3 reports that the T-test statistic comparing means of the sample (25.90)
and the population of university students (26.0) revealed no significant difference
i.e. p=0.636 (Ministry of Education, 2013; SARUA, 2012). This means that the
sample profile matched the population in relation to age, thus, allowing for
generalisability of findings.
Table 7.310- One-Sample T-test for Age Comparison with Student Population
Test Value = 26
T df Sig. (2-tailed) Mean Difference 95% Confidence Interval of the Difference
Lower Upper
Age -.473 863 .636 -.101 -.52 .32
With regard to field of study, while 49.2% of respondents were enrolled in business
related degrees, 46.8% were pursuing non-business degrees. The latter were
18.7% in engineering, applied sciences, information and communications
technology or the built environment; 11.9% in natural resources and agriculture-
related degrees; and, 18.1% were in other social sciences. This distribution was
important because the findings would be meaningful across different disciplines.
Extant literature indicates that prior entrepreneurial exposure has an effect on EI
(Krueger, 1993). In addition, it has been found to influence the relationship
between EE and EI (Fayolle et al., 2006b; Fayolle, 2007; Fayolle and Gailly, 2009;
Soriano, 2009). In this sample, 53% of respondents had either a parent or family
member who had started and run a business before. This proportion seemed to be
typical in developing countries in Africa because in a study in Namibia, the
Research Design and Implementation
157
proportion was 50% (Haase et al., 2011). For developing countries, this may be
typical due to low job prospects which may compel some individuals to consider
necessity entrepreneurship (Kelley et al., 2011). Lastly, the majority of
respondents (88.5%) either had no employment experience at all (71.2%) or had a
few months of internship (17.3%). This is the typical experience of an
undergraduate student in Zambia.
In assessing the effect of EE on EI, the majority of prior studies have been
criticised for not including a comparison group (Rideout and Gray, 2013).
Therefore, scholars call for studies that compare participants and non-participants
in EE (Oosterbeek et al., 2010; Souitaris et al., 2007). This sample achieved this
balance since 49% (426/878) of the respondents did not participate in any EE
compared to 51% (452/878) who did. In addition, when EE participants are
compared to non-participants, a chi-square test for independence indicated no
statistically significant difference in proportions of public and private universities in
the two groups, χ2(1, n=846) =0.929, p<0.335. Further, a chi-square test for
independence indicated no statistically significant difference in proportions of
females and males in the two groups, χ2(1, n= 849)=1.067, p<0.302. A T-test
executed to compare the mean age for EE participants (26.0 years) and non-
participants (25.8 years) indicates a statistically insignificant difference, t=1.365,
df=862, p=0.173. The statistically insignificant differences in age, gender and type
of university between EE participants and non-participants imply that the two
groups have similar demographic profiles. The only major difference is the
participation in EE.
Research Design and Implementation
158
7.3 Measurements and Scales – Quantitative Study
Items comprising the constructs for the quantitative study were believed to have
content validity based on three reasons. Firstly, construct items were adopted or
adapted from prior studies such as Busenitz et al. (2000), Liñán et al. (2011),
Krueger (1993), Souitaris et al. (2007), De Clercq et al. (2011), and Carter et al.
(2003). Secondly, the construct items were further filtered through extensive
discussions with researchers in the field and where necessary rephrased. Finally,
following survey data collection, the constructs were further assessed for validity
through principal component analyses using SPSS (Saunders et al., 2009). There
are two major advantages for adopting measures from prior studies. Firstly, the
questions have already been tested for reliability and validity. Secondly, findings in
subsequent research employing the same constructs can be compared to prior
studies (Gartner, 1989a; Thompson, 2009).
Perspectives on Measurement of EI and its Determinants
To begin with, EI is a self-acknowledged claim by a person that he/she intends to
set up a new business venture and plans to do so. This is a conscious state of
mind that precedes action (Ajzen, 2002; Shapero and Sokol, 1982; Thompson,
2009). In addition, all the factors influencing EI are expected to do so through their
effects on perceived feasibility and desirability of entrepreneurship (Davidsson,
2004; Hindle et al., 2009). The current study used perceptual measures in line with
the proposition that perceptions of the environment can be stronger predictors of
entrepreneurial actions than actual facts (Zahra, 1993; Zahra and Covin, 1995).
This also resonates with the proposition that individuals with high EI, based on
perceived feasibility and desirability, are more likely to start a venture than those
with low or no EI (Henley, 2007; Kautonen et al., 2013).
Research Design and Implementation
159
Furthermore, scale measures were used because the degree of EI might vary from
person to person. Perhaps, it might even vary for the same person at different
points of time depending on circumstances (Thompson 2009; Ajzen, 2011).
Whether or not someone has EI is not simply a yes or no question. Instead, it is a
matter of intention to start a business varying from very low to very high. While
Krueger et al. (2000) use a 1-item measure, “estimate the probability that you’ll
start your own business in the next 5 years” (p. 421), they acknowledge the
problems of reliability and validity of their single-item measure. For this reason,
they suggest that, to improve the design of entrepreneurship research, it might be
“valuable if future studies would employ multiple-item measures of key constructs
to reduce measurement error” (p.425).
Based on the foregoing considerations, multi-item Likert scales were adopted for
the dependent variable EI, its attitudinal antecedents, and the individual and
institutional factors. Tables 7.4 to 7.7 report the measures adopted/adapted. Each
of the scales comprised a set of items depicting the construct from different
angles. For each item, a 5-point Likert scale was used (1 being strongly disagree
and 5 being strongly agree) to enable respondents to indicate the extent to which
they agree to these items. For prior entrepreneurial exposure, the current study
followed the practice in prior research by using a combination of 5-point Likert
items and dichotomous items. In summary, the items used in the survey
questionnaire were meant to measure the following:
Research Design and Implementation
160
Dependent Variables (Table 7.4)
Entrepreneurial intention;
Perception of feasibility of entrepreneurship; and
Perception of desirability of entrepreneurship.
Independent Variables –Institutional Factors (Table 7.5)
Regulatory institution;
Normative institution; and
Cognitive institution.
Independent Variables – Individual Factors (Table 7.6)
Risk taking propensity;
Locus of control ;
Need for achievement; and
Prior entrepreneurial exposure.
Intervening Variables – Effectiveness of Entrepreneurship Education (Table 7.7)
Perceived learning (mastery of entrepreneurship skills and knowledge) from
EE;
Perceived involvement with practical approaches during EE (experiential
learning); and
Perceived access and interaction with relevant resources during EE.
Control Variables
Gender (male/female);
University type (private or public);
Age (actual); and
Field of study (business/non-business).
Research Design and Implementation
161
Table 7.411- Items on EI and its Attitudinal Antecedents
Desirability Liñán et al., 2011
Being an entrepreneur would entail great satisfaction for me (D1)
Among various options, I would rather be an entrepreneur (D2)
A career as an entrepreneur is attractive for me (D3)
If I had the opportunities and resources, I would like to start a firm (D4)
Being an entrepreneur implies more advantages than disadvantages to me (D5)
Feasibility Liñán et al., 2011
I can control the creation process of a new firm (F1)
I know the necessary practical details to start a firm (F2)
To start a firm and keep it working would be easy for me (F3)
I am prepared to start a viable firm (F4)
I know how to develop an entrepreneurial project (F5)
If I tried to start a firm, I would have a high probability of succeeding (F6)
Entrepreneurial Intention Kolvereid, 1996; Souitaris et al., 2007; Liñán et al., 2011
I am likely to pursue a career as an entrepreneur? (EI1)
I would prefer to be an entrepreneur (self-employed) as opposed to organisational employment (EI2)
I am attracted to a career as an entrepreneur (self-employed) (EI3)
Table 7.512- Items on Institutional Factors
Regulatory Institution Busenitz et al., 2000; De Clercq et al., 2011; Martinez et al., 2010
The government sponsors organisations that help new businesses to develop (REG1)
Even after failing in an earlier business, entrepreneurs are assisted by
the government in start-ups (REG2)
Local and central governments have special support available for individuals who
want to start a new business (REG3)
The government sets aside contracts for new small businesses (REG4)
Government organisations in this country assist individuals starting their own businesses (REG5)
In my country there is sufficient financial support available for new start-ups (REG6)
In my country universities/learning institutions provide advisory and development
support for new businesses (REG7)
In my country there are sufficient government subsidies available for new firms (REG8)
In my country state laws, rules and regulations are adverse to starting and running a business (REG9) ®
Normative Institution Busenitz et al., 2000
Entrepreneurs are admired in this country (NORM1)
People in this country tend to greatly admire those who start their own businesses (NORM2)
In this country, innovative and creative thinking is viewed as the route to success (NORM3)
Turning new ideas into businesses is an admired career path in this country (NORM4)
Research Design and Implementation
162
Cognitive Institution Busenitz et al., 2000
In my country most people know where to find information about markets for their products (COG1)
In my country those who intend to start new businesses know how to manage risk (COG2)
In my country individuals know how to legally register and protect a new business (COG3)
® Reverse coded
Table 7.613- Items on Individual Factors
Need for Achievement Walter et al., 2011; Luethje and Franke, 2004
Hard work is always something I engage myself to (NAch1)
I frequently think about ways I could earn a lot of money (NAch2)
I believe I would enjoy having authority over other people (NAch3)
I find satisfaction in exceeding my previous performance even if I do not outperform others (NAch4)
I would like an important job where people look up to me (NAch5)
I care about performing better than others on a task (NAch6)
I would rather do tasks which appear challenging and difficult than the ones in which
I feel confident and relaxed (NAch7)
Locus of Control Lüthje and Franke, 2003; Chen et al.,1998; Mueller and Thomas, 2001
When I get what I want, it is usually because I am lucky (LC1) ®
When I make plans I am almost certain I can make them work (LC2)
Every time I try to get ahead something or somebody stops me (LC3) ®
When I get what I want it is usually because I worked hard for it (LC4)
I have enough control over the direction of my life (LC5)
Whether or not I am successful in life depends mostly on my ability (LC6)
Risk Taking Propensity Zhao et al., 2005; Lüthje and Franke, 2003
I like trying new things (RTP1)
I am willing to take significant risk if the possible rewards are high enough (RTP2)
When I am about to do something, I really dislike the idea that I do not know
what is going to happen (RTP3) ®
I have taken a risk in the last six months (RTP4)
I enjoy the excitement of uncertainty and risk (RTP5)
When I travel I tend to use new routes (RTP6)
Prior Entrepreneurial Exposure Krueger, 1993; Liñán et al., 2011; BarNir et al., 2011
Has your parent started and run a business before? (Yes/No)
To what extent would you consider that parent to be a good entrepreneur? ( Scale)
Has a family member(s) other than a parent started and run a business before? (Yes/No)
To what extent would you consider the family member (s) to be (a) good entrepreneur (s)? (Scale)
Have you ever worked in family business before? (Yes/No)
Have you started and run a business before? (Yes/No)
Have you ever worked for a small or new business? (Yes/No) – checked against staff numbers.
® Reverse coded
Research Design and Implementation
163
Table 7.714- Items on Effectiveness of EE
Perceived Learning and Skills acquired Fayolle et al.,2006; Souitaris et al., 2007; Johannisson, 1991
Increase your understanding of the actions someone has to take in order to start a business (i.e. what needs to be done?) (PLS1)
Increase your understanding of the attitudes, values and motivation of entrepreneurs (i.e. why do entrepreneurs act?) (PLS2)
Enhance your practical management skills in order to start a business (i.e. how do you start the venture?) (PLS3)
Enhance your ability to identify an opportunity (i.e. when do you need to act?) (PLS4)
Enhance your ability to develop networks (i.e. who do you need to know)? (PLS5)
Interaction and Access to Resources Souitaris et al., 2007
Seed funding from the university (IAR1)
Advice from technology transfer office or business development office (IAR2)
Advice from faculty or lecturers/ business development services (IAR2)
Advice from classmates (IAR4)
A pool of university technology (IAR5)
A pool of entrepreneurial minded classmates for building a team (IAR6)
Research resources ( e.g. to assess feasibility) (IAR7)
Networking events (IAR8)
Physical space for meetings (IAR9)
Business plan competitions (testing ground for the idea) (IAR10)
Referrals to investors and other funding organisations (IAR11)
Practical Involvement in Entrepreneurship (Experiential learning) Neck and Greene, 2011; Herrero and van Dorp, 2012; McMullan and Boberg,1991
Identifying opportunities or generating business ideas (PI1)
Developing, presenting and defending a business model (PI2)
Hands on projects or assignments undertaken (PI3)
Developing, presenting and defending a business plan (PI4)
Work placement or internship with a small or medium-sized business (PI5)
Work placement or internship with large firm (PI6)
Actual venture creation or start up business (PI7)
Business simulation games/projects (PI8)
7.4 Construct Validity Analyses Results- Quantitative Study
To further assess internal validity, factor analyses were conducted to evaluate
construct validity i.e. assess the extent to which items in a scale measure the
same construct theme (Saunders et al., 2009). The procedures were based on
guidelines in the extant literature (Hair et al., 2006; Burns and Burns, 2008;
Pallant, 2010). After recoding the reversed items, principal component analyses
Research Design and Implementation
164
(PCA) were executed to obtain an empirical summary of the data set (Pallant,
2010). Since both the orthogonal (Varimax) and oblique (Oblimin) factor rotation
methods yielded the same results, only Varimax results are reported (Busenitz et
al., 2000).
7.4.1. Construct Validity for Attitudinal Antecedents of EI
Prior to PCA, the suitability of the data and sample for factor analysis was
assessed. Bartlett’s Test of Sphericity (sig=0.000, df=78) was significant,
indicating that sufficient correlations existed among the variables (Burns and
Burns, 2008). The Kaizer-Meyer-Olkin (KMO) value of 0.881 exceeded the
minimum recommended value of 0.50 (Kaiser 1970, 1974; Hair et. al., 2006,
p.115). This meant that the sample was adequate. Lastly, the data set had a very
high respondent to variable ratio. Meeting these criteria supported the factorability
of the correlation matrix (Hair et al., 2006, p.128; Pallant, 2010).
PCA revealed a 2 component solution with cumulative total variance explained of
59.390%. Table 7.8 shows the variance explained per factor i.e. factor 1, 43.855%;
and, factor 2, 15.535%. An inspection of the scree plot (Cattel, 1966) revealed a
clear break after the second factor. Furthermore, the Varimax rotated solution
revealed a simple and clear structure (Thurstone, 1947). This was supported by
both factors showing a number of high loadings and all variables loading
substantially on only one factor, thus, proving unidimentionality of items (Hair et.
al., 2006, p.136). Items were retained in a factor if they had a loading at or above
0.40 on that factor, and the differences between one loading and other cross-
loadings were more than 0.30 (Burns and Burns, 2008; Howell et al., 2005; Wang
and Ahmed, 2009). Interpretation of the 2 factors was consistent with prior
research (Douglas and Shepherd, 2002; Fitzsimmons and Douglas, 2011; Liñán,
2008; Liñán, 2008; Liñán and Chen, 2009; Liñán et al., 2011a; Souitaris et al.,
Research Design and Implementation
165
2007) that perceptions of desirability and feasibility are separate constructs for
assessing attitudinal antecedents of EI.
Table 7.815- Item and Cross-Loadings for Attitudinal Antecedents of EI
Note: Desirability=items D1 to D5, Feasibility=items F1 to F6
7.4.2 Construct Validity for Institutional Factors
Prior to PCA, all the necessary conditions for sample and data suitability were
assessed: correlation matrix with coefficients of 0.30 and above, significant
Bartlett’s Test of Sphericity (sig=0.000, df=78), and KMO value of 0.814. All
supported sampling adequacy. PCA revealed a 3 component solution with
cumulative total variance explained of 59.239%. Based on Cattel’s scree plot and
Varimax rotated solution, the 3-factor structure was clear. Interpretation of the
three factors was consistent with prior research (Almobaireek and Manolova,
2012; Busenitz et al., 2000; Manolova et al., 2008; Spencer and Gomez, 2004)
that cognitive, normative and regulatory institutions be regarded as separate
constructs for assessing country institutional profile for entrepreneurship (Table
7.9).
Factor 1 Factor 2
Retained Items
D1 0.843 0.165
D2 0.794 0.147
D3 0.786 0.187
D4 0.755 0.150
D5 0.628 0.241
F1 0.185 0.790
F2 0.125 0.738
F3 0.037 0.697
F4 0.306 0.679
F6 0.206 0.589
Dropped Item
F5 -0.019 0.268
Eigen Value 4.385 1.554
Percent of Variance 43.855 15.535
Research Design and Implementation
166
Table 7.916- Item and Cross-Loadings for Institutional Factors
Note: Regulatory Dimension=REG1 to REG9, Normative Dimension= NORM1 to NORM 4, Cognitive Dimension=COG1 to COG3
7.4.3 Construct Validity for Individual Factors
Prior to PCA, the suitability of data and sample for factor analysis was assessed;
correlation matrix with coefficients of 0.30 and above, significant (sig=0.000,
df=78) Bartlett’s Test of Sphericity (Bartlett, 1954), and KMO value of 0.853, all
supported sampling adequacy. PCA revealed a three component solution with
cumulative total variance explained of 51.833%. Based on Cattel’s scree test
(Cattell, 1966) and Varimax rotated solution, a simple and clear structure of 3
factors emerged (Burns and Burns, 2008; Kaiser, 1970; Kaiser and Rice, 1974;
Thurstone, 1947). Interpretation of the three factors was consistent with prior
research (Gomez-Mejia and Balkin, 1989; Lüthje and Franke, 2003; Meertens and
Lion, 2008; Mueller and Thomas, 2001; Walter et al., 2011; Zhao et al., 2005) that
need for achievement, locus of control and risk taking propensity be regarded as
separate constructs for assessing individual characteristics’ influence on EI (Table
7. 10).
Factor 1 Factor 2 Factor 3
Retained Items
REG1 0.763 0.112 0.085
REG2 0.753 -0.022 0.079
REG3 0.746 0.135 0.089
REG4 0.726 0.005 0.129
REG5 0.687 0.118 0.083
NORM1 0.011 0.820 0.038
NORM2 0.036 0.807 0.033
NORM3 0.172 0.754 0.193
NORM4 0.105 0.722 0.146
COG1 0.185 0.097 0.814
COG2 0.186 0.088 0.813
COG3 0.099 0.166 0.775
Dropped Items
REG6 0.532 0.060 0.432
REG7 0.307 0.207 0.343
REG8 0.572 0.010 0.435
REG9 -0.320 -0.018 -0.246
Eigen Value 4.065 2.160 1.476
Percent of Variance 31.266 16.616 11.358
Research Design and Implementation
167
Table 7.1017- Item and Cross-Loadings for Individual Factors
NB: Need for Achievement=NAch1 to NAch7, Locus of Control=LC1 to LC6, Risk Taking propensity = RTP1 to RTP 6
7.4.4 Construct Validity for Effectiveness of EE
Prior to PCA, the suitability of the data and sample for factor analysis was
assessed: correlation matrix with coefficients of 0.30 and above, significant
Bartlett’s Test of Sphericity (sig=0.000, df=91), and KMO value of 0.883 indicated
that sampling was adequate. PCA revealed a three component solution with
cumulative total variance explained of 62.087%. Based on Cattel’s scree test and
Varimax rotated solution, three factors emerged. The interpretation of the factors
was consistent with prior research (Herrero and Van Dorp, 2012; Johannisson,
1991; Johannisson et al., 1998; McMullan and Boberg, 1991; Souitaris et al.,
2007) that perceived learning and access to resources be considered as separate
constructs for assessing participants’ perception of effectiveness of EE. The
practical approaches (experiential learning) construct was being generated and
validated for the first time (Table 7.11).
Factor 1 Factor 2 Factor 3
Retained Items
NAch2 0.769 0.312 0.151
NAch3 0.809 0.108 0.097
NAch6 0.755 0.238 -0.022
NAch4 0.708 0.116 0.145
LC2 0.188 0.648 0.183
LC4 0.246 0.728 0.061
LC6 0.139 0.713 0.065
LC5 0.099 0.656 0.04
RTP1 0.174 0.209 0.525
RTP2 0.168 0.111 0.483
RTP4 0.044 0.093 0.589
RTP5 -0.006 -0.019 0.764
RTP6 0.062 0.002 0.636
Dropped Items
NAch1 0.413 0.702 0.096
NAch5 0.442 0.506 0.053
NAch7 0.385 0.609 0.180
LC1 0.244 0.474 0.031
LC3 0.255 0.498 -0.131
RTP3 0.448 0.119 0.211
Eigen Value 3.944 1.587 1.208
Percent of Variance 30.338 12.204 9.291
Research Design and Implementation
168
Table 7.1118- Item and Cross-Loadings for Effectiveness of EE
Note: Perceived Learning and Skills from EE =PLS1 to PLS5; Interaction with and Access to Resources=IAR1 to IAR11; Practical Approaches/Involvement (Experiential Learning) = PI1 to PI8
7.5 Measurement Reliability Analyses Results-Quantitative Study
Reliability refers to consistency and stability of measures that allow for replication
of research (Burns and Burns, 2008; Davis, 1964; Peterson, 1994; Tabachnick
and Fidell, 2012). It is an assessment of the degree of consistency between
multiple measurements of a variable (Hair et al., 2006, p.137). A widely used
measure of reliability is internal consistency. It assesses the consistency among
variables (items) in a construct. Its rationale is that the individual items or
indicators of the scale should all be measuring the same construct and, thus, be
highly inter-correlated (Nunnally and Bernstein, 1978). The most widely used
indicator of internal consistency is Cronbach’s alpha coefficient (i.e. reliability
coefficient). It assesses the consistency of the entire scale (Cronbach, 1951; Hair
et al., 2006; Nunnally and Bernstein, 1978; Peter, 1979). Caution must be
exercised because the higher the number of items in a scale, the larger the
Factor 1 Factor 2 Factor 3
Retained Items
PLS1 0.856 0.139 0.050
PLS2 0.801 0.168 0.058
PLS3 0.764 0.207 0.196
PLS4 0.754 0.129 0.214
PLS5 0.715 0.129 0.301
IAR3 0.268 0.730 0.074
IAR4 0.139 0.729 0.110
IAR5 0.048 0.693 0.360
IAR6 0.284 0.668 0.185
IAR7 0.136 0.615 0.193
IAR8 -0.001 0.586 0.202
PI5 0.150 0.187 0.828
PI6 0.140 0.192 0.799
PI7 0.188 0.268 0.696
PI8 0.267 0.233 0.566
Dropped Items
IAR1 -0.169 0.512 0.273
IAR2 0.114 0.569 0.468
IAR9 0.088 0.525 0.543
IAR10 0.006 0.641 0.361
IAR11 -0.147 0.665 0.337
PI1 0.555 0.327 0.098
PI2 0.588 0.506 0.129
PI3 0.536 0.239 0.24
PI4 0.492 0.533 0.140
Eigen Value 5.602 1.853 1.238
Percent of Variance 40.014 13.234 8.839
Research Design and Implementation
169
reliability coefficient. The generally preferred Cronbach’s alpha value is 0.70
(Andrews et al., 1991; Cronbach, 1951; DeVellis, 2003; Pallant, 2010). Since
reliability of a scale can vary depending on the sample, it is necessary to check
that each of the scales used is reliable. It is also necessary to ‘reverse’ any
negatively worded items before reliability analyses (Pallant, 2010; Burns and
Burns, 2008). In the current study, all the internal reliability tests yielded
coefficients above the minimum acceptable value of 0.60 (Brace et al., 2009).
7.5.1 Reliability Analyses for Desirability, Feasibility and EI
Table 7.12 reports the results of reliability analyses. The reliability coefficients for
feasibility and desirability were markedly above the higher threshold of 0.70
(Fitzsimmons and Douglas, 2011; Liñán and Chen, 2009; Liñán et al., 2011a). In
addition, the reliability coefficient for EI was slightly above the higher threshold of
0.70 (Iakovleva et al., 2011; Kolvereid, 1996a; Pallant, 2010; Souitaris et al., 2007;
Tkachev and Kolvereid, 1999). Nevertheless, all the alpha values were above the
threshold of 0.70 (Nunnally and Bernstein, 1978; Brace et al., 2009).
Table 7.1219- Reliability Analyses of Attitudinal Antecedents and EI
Item Number Corrected Item-Total Correlation α if Item Deleted
Desirability (α=0.85)
D1 0.755 0.801
D2 0.685 0.819
D3 0.690 0.817
D4 0.662 0.827
D5 0.565 0.852
Feasibility (α=0.79)
F1 0.649 0.716
F2 0.554 0.748
F3 0.497 0.766
F4 0.578 0.739
F6 0.535 0.754
Entrepreneurial Intention (α=0.734)
EI1 0.497 0.701
EI2 0.550 0.469
EI3 0.542 0.506
Research Design and Implementation
170
7.5.2 Reliability Analyses for Institutional Factors
Table 7.13 shows the results of reliability analyses. Clearly, all the reliability
coefficients for regulatory, cognitive and normative institutions were above the
threshold of 0.70 (Busenitz et al., 2000; Manolova et al., 2008; Nunnally amd
Bernstein, 1978).
Table 7.1320- Reliability Analyses for Institutional Factors
7.5.3 Reliability Analyses for Individual Factors
Table 7.14 reports the results of reliability analyses. Firstly, the need for
achievement scale’s coefficient of 0.80 was above the threshold of 0.70 (Ahmad,
2010; Ahmed, 1985; Cassidy and Lynn, 1989; Kristiansen and Indarti, 2004;
Nunnally and Bernstein, 1978; Steers and Braunstein, 1976; Walter et al., 2011).
Secondly, the coefficient of 0.70 for the locus of control scale was also at the
recommended higher threshold (Kristiansen and Indarti, 2004; Luethje and
Franke, 2004; Lüthje and Franke, 2003; Mueller and Thomas, 2001). Thirdly, the
risk taking propensity scale’s coefficient of 0.62 was higher than the minimum
acceptable threshold of 0.60 for social sciences research (Brace et al., 2009;
Luethje and Franke, 2004; Meertens and Lion, 2008; Zhao et al., 2005).
Item Number Corrected Item-Total Correlation α if Item Deleted
Regulatory Dimension (α=0.81)
REG1 0.630 0.766
REG2 0.609 0.772
REG 3 0.614 0.770
REG4 0.585 0.777
REG5 0.556 0.783
Normative Dimension (α=0.80)
NORM1 0.624 0.735
NORM2 0.608 0.743
NORM3 0.627 0.732
NORM4 0.568 0.765
Cognitive Dimension (α=0.77)
COG2 0.618 0.675
COG1 0.628 0.656
COG3 0.565 0.734
Research Design and Implementation
171
Table 7.1421- Reliability Analyses for Individual Factors
7.5.4 Reliability Analyses for Effectiveness of EE
Table 7.15 reports the results of reliability analyses. Firstly, the scale for perceived
learning had a coefficient of 0.87, exceeding the upper threshold of 0.70 (Souitaris
et al., 2007). Secondly, the scale for perceived practical approaches (experiential
learning) and the scale for perceived access and interaction with relevant
resources both had reliability coefficients of 0.81. This alpha value also exceeded
the upper threshold of 0.70 (Nunnally and Bernstein, 1978).
Table 7.1522- Reliability Analyses of Effectiveness of EE
Item Number Corrected Item-Total Correlation α if Item Deleted
Need for Achievement (α=0.80)
NAch2 0.690 0.714
NAch3 0.636 0.735
NAch4 0.527 0.786
NAch6 0.602 0.751
Locus of Control (α=0.70 )
LC2 0.480 0.630
LC4 0.556 0.586
LC5 0.407 0.679
LC6 0.485 0.627
Risk Taking Propensity (α=0.62)
RTP1 0.352 0.563
RTP2 0.377 0.555
RTP4 0.333 0.580
RTP5 0.438 0.516
RTP6 0.346 0.566
Item Number Corrected Item-Total Correlation α if Item Deleted
Perceived Learning and Skills Acquisition (α=0.87)
PLS1 0.737 0.833
PLS2 0.678 0.847
PLS3 0.712 0.838
PLS4 0.681 0.846
PLS5 0.672 0.849
Interaction and Access to Resources (α=0.81)
IAR3 0.604 0.776
IAR4 0.571 0.784
IAR5 0.631 0.770
IAR6 0.593 0.779
IAR7 0.508 0.797
IAR8 0.533 0.792
Practical Involvement ( α=0.81)
PI5 0.704 0.715
PI6 0.655 0.740
PI7 0.611 0.763
PI8 0.521 0.801
Research Design and Implementation
172
7.6 Statistical Controls and Common Methods Bias –Quantitative Study
Statistical checks were conducted to ensure that the data met various
requirements necessary to conduct further bivariate and multivariate analyses.
Specifically, checks for missing data, outliers, normality and common method bias
were conducted.
Missing Data and Outliers A thorough check of the descriptive statistics revealed that missing data for the
variables and respondents ranged between 0.1% and 4.1%. Missing data under
10% for each respondent or variable can generally be ignored because it does not
have a significant effect on any analyses (Hair et al., 2006). Notwithstanding, in
order not to limit the sample size, the case selection option used for statistical
analyses was Exclude Cases Pairwise instead of Exclude Cases Listwise
(Pallant, 2010). With regard to outliers, inspection of boxplots and comparison of
actual means with the 5% trimmed means for the variables and factors revealed
no extreme scores with strong influence on the means. Thus, no significant
influence of outliers was present (Pallant, 2010).
Tests of Normality Most parametric multivariate techniques require that data is normally distributed to
reduce the risk of results being biased and flawed (Hair et al., 2006). Violations of
normality can have serious effects in small samples (less than 50 respondents),
but the impact effectively diminishes when sample sizes reach 200 respondents
and beyond (Hair et al., 2006, p. 86; Pallant, 2010). Thus, with a large survey
sample in the current study, the impact of any violation of normality would be
insignificant. Notwithstanding, tests checking violation of normality using
Kolmogorov-Smirnov statistic were non-significant (p>0.05).
Research Design and Implementation
173
Common Methods Bias (CMB) Checks CMB manifests when variance in the variables is partially attributable to the
measurement method rather than to the constructs the measures represent
(Podsakoff et al., 2003). Unlike random bias, systematic bias is a problem
because it may be one of the sources of measurement error. This would threaten
the validity of findings (Bagozzi and Yi, 1991; Bagozzi et al., 1991; Nunnally and
Bernstein, 1978). Besides ensuring that some construct items were reverse-coded
to mitigate the bias of acquiescence (Liñán et al., 2011a), Harman’s one factor
test, the most widely used technique, was conducted to statistically check for CMB
(Carr and Sequeira, 2007; Podsakoff et al., 2003). All items from all constructs in
the study were loaded into an exploratory factor analysis to determine whether the
majority of the variance could be accounted for by one general factor. The
rationale is that if a substantial amount of CMB is present, either (a) a single factor
will emerge from the factor analysis or (b) one general factor will account for the
majority of the covariance among the measures (Campbell and Fiske, 1959;
Meade et al., 2007; Podsakoff et al., 2003). In this study, factor analysis of all
items revealed a 12-factor solution (in line with the number of constructs in this
research) with cumulative total variance of 60.403%. The first factor accounted for
16.686% of the variance. Therefore, CMB was not a problem in this research.
7.7 Conclusions
This chapter has discussed research design choices comprising philosophy,
approach, strategies and data collection techniques and procedures. To avoid bias
from utilising one particular methodology, this research purposely employed a
concurrent triangulation strategy. The strategy was intended for model testing and
in-depth understanding of the research problems from the Zambian context. The
qualitative research was undertaken based on semi-structured interviews and the
Research Design and Implementation
174
quantitative research was based on a survey. It was believed that the triangulation
research strategy would determine whether there is convergence or divergence of
findings on the social phenomenon.
The chapter discusses the population, sampling procedures and demographic
profiles for both the qualitative and quantitative research. The chapter also
highlights the measurement imperatives with regard to validity and reliability.
Finally, the chapter shows the statistical tests to develop constructs. The next
chapter (chapter 8) presents and discusses results of the interviews. Thereafter,
chapter 9 presents and discusses results of the survey.
175
CHAPTER 8: QUALITATIVE RESEARCH FINDINGS
8.0 Introduction
The preceding chapter discusses the research design and procedures for data
collection and analyses. This chapter discusses the findings of the qualitative
research which was undertaken to provide an in-depth understanding of the
conceptual model. The chapter synthesises results of 13 semi-structured
interviews in Zambia. Firstly, section 8.1 demonstrates the effects of individual and
institutional factors on entrepreneurial intention (EI). Secondly, section 8.2 focuses
on the intervening role of entrepreneurship education (EE) in the relationships
between individual and institutional factors and EI. Thirdly, section 8.3 explains the
implications of the evidence from the interviews on the conceptual model. Fourthly,
section 8.4 draws the overall conclusion that indeed EE has an intervening role;
specifically, it mediates the effects of individual and institutional factors on EI.
8.1 Findings on Individual and Institutional Factors Influencing EI
An in-depth discussion of the results derived from the 13 interviews is provided in
subsection 8.1.1 for institutional factors and subsection 8.1.2 for individual factors.
8.1.1 Institutional Factors’ Influence on EI
According to Busenitz et al.’s (2000) study on the effect of the entrepreneurial
environment on entrepreneurial activity, the regulatory institution refers to laws,
regulations, administrative and support mechanisms from government and other
organisations that facilitate not only business start-ups but also activities of small
and medium-sized enterprises (SMEs). Cognitive institution includes generally
shared knowledge within society about how to start and manage a business.
Qualitative Research Findings
176
Lastly, normative institution captures societal admiration of entrepreneurship and
innovation.
8.1.1.1 Regulatory Institution’s Influence on EI
Evidence from the interviews indicates that regulatory mechanisms to support
business start-up are vital because they lead to perception that entrepreneurship
is not only possible but also worthwhile. Below are quotes from the interviews:
“…for me, I think that support from government and other relevant institutions creates an environment conducive to entrepreneurship and, thus, stimulates entrepreneurship. Support also signals that business start-up is a good thing for individuals and, therefore, important for society. Support either by way of simplified laws, advisory services and access to affordable start-up finance promotes the status of entrepreneurship as an important endeavour. So support matters in the intention to start a business.” Educator 2
“…from experience, I can say that government and other institutions’ support affects the intention to start a business in many ways but mainly by reducing barriers. Therefore, for would-be entrepreneurs, availability of support makes them begin to think that business start-up is achievable. I consistently noticed that there are individuals who started their businesses because assistance for start-ups became available from our institution. In other words, these individuals would not have started if support was not available.” Practitioner 2
The evidence indicates that a favourable policy may promote entrepreneurship to
a high status in society. It also increases entrepreneurs’ confidence by thinking
that starting and growing a business is possible. Specifically, the 13 interviews
outline four major benefits the support mechanism can offer. These benefits
include: a) simplified regulations on business operations and lower business
formalisation costs (12); b) access to markets (13); c) access to affordable (low
cost) finance (13); and, d) advisory and training services as well as affordable
relevant infrastructure and technology (13).
a) The evidence indicates that simplified regulations on business operations and
lower costs for fulfilling legal requirements (formalisation costs) are conducive to
entrepreneurship. Such an environment would lead to the perception that legal
Qualitative Research Findings
177
requirements can be met. For instance, Student 1 explains that “Simplifying
rules/regulations for taxation, registration of businesses…would increase the
number of people willing to start a business because they will perceive that it is
less complicated and, therefore, easily achievable.” In addition, Educator 1
explains that “Simplified laws would also be helpful ...most people complain about
too many complicated rules that would-be entrepreneurs have to abide by at the
time of firm formation and during operations.”
The foregoing perspectives are further clarified by Educators 1 and 3 as well as
Student 2 who suggest that, in order to promote entrepreneurship, there is need to
reduce business registration fees, business rates and rents for new businesses.
Practitioner1 cites an example that one government enterprise support institution
has collaborated with the Zambian tax authorities on a 3-year and 5-year tax
holiday scheme for registered urban and rural start-ups, respectively. This allows
start-ups that register with this facility to operate with no concern over corporate
tax. Student 2 notes that some critical business formalisation services can only be
accessed via provincial headquarters (regional centres). This creates a barrier
against nascent entrepreneurs because of travel cost implications. Formalisation
services include business registration/incorporation, registrations for tax, social
security, property, holiday schemes and access to start-up incentives.
Table 8.1 shows selected comparative contextual details based on data from the
World Bank’s ranking of 189 economies in terms of overall ease of doing and
starting business. Clearly, the data on Zambia shows that ease of starting a
business improved during the year 2013 and was generally better than the
average ranking of sub-Saharan Africa. Specifically, for ease of starting a
business, the improvement in Zambia’s rank from 70 (2013) to 45 (2014) was
mainly due to the elimination of the requirement for actual paid-in minimum capital
Qualitative Research Findings
178
at the time of starting up a business. It was also because the country raised the
threshold for Value Added Tax registration from Zambian Kwacha 200,000 (i.e.
US$36,000 per annum) to Zambian Kwacha 800,000 (i.e. US$150,000 per
annum). However, many challenges for business start-up still remain. For
example, the cost for registration of a new business is 26.8% of per capital income
(2012 Zambia per capita income: US$1350) compared to the best performing
economies in that category i.e. Slovenia (0%), New Zealand (0.3%) and South
Africa (0.3%). Additionally, a business has to make tax payments 38 times
annually, far more than the best performing economy i.e. 3 times in Hong Kong.
Similarly, the 183 hours per annum spent on tax compliance issues for a business
is higher than the best performing economy i.e. United Arab Emirates at 12 hours.
In fact, as Educator 2 and Student 3 observe, to successfully complete each start-
up registration procedure takes more than a week, contrary to the standard of 6.5
days reported globally for the whole process. Educator 2 explains that, in reality,
more than 40 days are required to fully register a new retail business. Lastly, in
relation to business registration procedures, despite the idea of a one-stop shop
having been implemented in the capital city in 2009, it is yet to be decentralised to
the rest of the country.
Qualitative Research Findings
179
Table 8.123- Comparative Ease of Starting and Doing Business in Zambia
Source: World Bank’s www.doingbusiness.org accessed on 19 February 2014 16:00 hours, UK
b) The interviews indicate that policies, legislation and mechanisms facilitating
access to markets for new businesses would encourage more people to start a
business. For instance, Educator 2 explains that “…If government sets aside
contracts for SMEs, more individuals will be encouraged to start businesses
because access to markets, especially at the beginning of a business, is always
difficult. It is one of the determinants of success or failure.” To clarify this,
Practitioner 2 cites a preferential procurement initiative by the Zambian
government:
“We have realised that availability and access to markets for SMEs is key support that would influence start-up intention, and even SMEs’ success… We think it can reduce barriers. As a result, among our institution’s empowerment pillars for citizens’ businesses, the government policy and legislation for preferential procurement initiative has prescribed that over the next five years a percentage of government expenditure on procurement of services and goods by various departments/institutions will be channelled toward SMEs that are owned or managed by citizens.”
Practitioner 2
From the forgoing evidence, any government policy, legislation or mechanisms
intending to facilitate access to markets is likely to be conducive to start-ups.
Qualitative Research Findings
180
When these are available, more potential entrepreneurs will consider starting a
business.
c) The interviews indicate that policies, legislation and mechanisms that facilitate
access to affordable (low cost) finance not only promote the status of
entrepreneurship in society but also reduce barriers. For instance, Student 4
explains that government initiatives to facilitate access to low-cost finance are
signals that business creation is important. For potential entrepreneurs, this not
only makes business start-up desirable but also realistic. Below is a quote:
“Even if an individual is able to identify an opportunity that he or she believes can be turned into a profitable business, and even if an individual is able to develop a business plan around such an idea, he or she will not be able to make it a reality if affordable start-up capital cannot be accessed. So for me this is a major support element that should be in place to promote entrepreneurship.” Student 6
The above perspective is further clarified by Practitioners 1 and 2. In their
experience, low cost debt finance enabled and encouraged people who would
never have considered starting a business to have a go. This view is consistent
with prior research (Gaspar, 2009). In Zambia, 70% of new businesses depend on
entrepreneurs’ own savings or help from family/friends for start-up capital.
Therefore, difficulties in accessing debt finance for start-up limits new venture
creation (Bank of Zambia FinScope, 2010).
Prior studies have shown that capital requirements and availability of financial
resources affect entrepreneurial propensity (Baumol et al., 2007; Ho and Wong,
2007; Van Stel et al., 2007). Indeed, low interest rates lead to an increase in new
business start-ups (Audretsch and Acs, 1994; Highfield and Smiley, 1987).
Furthermore, the three practitioners acknowledge that the current support may not
be adequate to cater for many nascent entrepreneurs. This is because of
government budgetary constraints. Students 1 and 5 indicate that while certain
Qualitative Research Findings
181
level of financial support is available, access is not straight forward. The
procedural requirements to access the debt finance are often complicated.
Sometimes they not only depend on whom one knows within the institution or
government but also whether one has collateral and a viable business plan. Only
few people may be able to meet these conditions, let alone the youths who are at
the beginning of their careers. Furthermore, the evidence indicates that financial,
government and non-government institutions that provide debt finance for start-
ups experience high default rates in loan repayment. Some of the experiences of
practitioners on this issue are highlighted in the quotes below.
“Some people we have dealt with in this scheme as we follow them up for repayment clearly do not seem to have a proper understanding of the fundamentals of running a business. I begin to question even their motives…whether we have a moral hazard were some people did not have business intention but just wanted to access the money as a hand-out! I think we need to find a better way of distinguishing those who are serious and mean well from those who are not serious at the time of considering the loan application. Most people though are now realising that we are serious with repayment as some are facing litigation because of default while others have assets they pledged as collateral being repossessed. So I think that when we resume receiving applications, we are going to attract those who are serious because people now know the consequences of default… Currently, loan repayment default rates are too high.” Practitioner 1
“Our experience is that it does not matter whether financial support comes from government or third sector organisations; it does not matter whether we are dealing with youths or mature individuals or groups. As long as the entrepreneur is not using his/her own money, managing the process of repayment is a big challenge for the lender especially if there is no collateral. Unless the individual is really focused and disciplined to establish his or her business, collateral acts as a deterrent. For those that go to the bank to borrow and they are asked for collateral, they work hard to repay the facility. Even when the business has not done well, some still find a way of paying back.” Practitioner 2
Interviewees indicate that the importance of facilitating access to debt finance
cannot be overemphasised. However, there is need for structured mechanisms to
ensure that financial resources are not only allocated to the intended purposes but
they are also given to capable individuals. This would mitigate wastage.
Practitioner 2, Educator 3 and Student 3 suggest that only individuals meeting
Qualitative Research Findings
182
certain conditions should have access to debt finance. For example, individuals
who show personal initiative by starting businesses on their own and are ready to
work under strict financial conditions should be considered.
d) Lastly, the evidence suggests that accessible sustained business advisory
services and access to affordable infrastructure and technology would result in
positive entrepreneurial outcomes. Educators 2 and 3 propose that mentoring
services for nascent and fledgling entrepreneurs would help build capacity
necessary for success. Such support would also assure potential entrepreneurs
that there is help available on the entrepreneurial journey. This is clarified by
Practitioner 3’s experience that potential entrepreneurs who receive business
advisory services are more likely to successfully start and manage a business.
Recipients of such support develop in skills and become more confident in their
abilities. Below are quotes from the interviews on the need for holistic support.
“ …in my experience, financial support should go with entrepreneurship training and advisory services as a prerequisite so that those who apply for such financial support have capacity not only to start but also to operate and grow a business until they become reliable and serious entities.”
Practitioner 2
“In my view, appropriate support should not only be about money but should include machinery, buildings (infrastructure) for operating from and from which new entrepreneurs can also be trained in various skills such as marketing, packaging and distribution to help them make quality products and transport the product to the right market. This will help them get established. I think that skills, buildings (infrastructure for operations) and money is the best combination that we have not had so far rather than just offer money.” Educator 3
“…business development services…would give confidence to people starting a business that help is available if they get stuck in the process of starting and running a business.” Student 3
“It would be better if business incubation services are established to provide continuous support to those starting. Infrastructure such as premises to operate from for those who are still getting established will also be appropriate.” Student 4
“Imparting skills on how to run and grow a business is very critical. I say so because a number of people may even have some money to start
Qualitative Research Findings
183
something but lack adequate knowledge about proper business practices such as cash flow management, pricing, marketing, evaluating a business idea, identifying business opportunities, strategies for growing a business. Skills training offered could be short courses but they should be on a sustained basis.” Student 5
Lastly, Practitioner 1 cites an example involving the Zambian government’s
Ministry of Youth and Sports which runs an empowerment scheme for youth out of
school/work. In this scheme, once a loan for start-up capital has been approved,
the nascent entrepreneur is required to undergo some business practices training
for a month. However, as Practitioner 1 and Student 3 observe, this training only
occurs at pre-start-up phase. What would be even more impactful are sustained
business advisory, development and monitoring services during the fledgling
period (0 to 3.5 years). This perspective is consistent with the GEM observations
that, given the challenges of starting a new business, many fledgling businesses
fail within 3.5 years (Kelley et al., 2011; Kelley et al., 2012; Martínez et al., 2010).
The GEM observations are based on 54 developing and developed economies
surveyed in 2011. The GEM survey did not include Zambia.
Overall Observation on the Effect of Regulatory Institution on EI
In a nutshell, favourable regulatory mechanisms comprising access to finance,
sustained business advisory and training services, simplified regulations on
business operations, lower formalisation costs, access to markets as well as
affordable relevant infrastructure and technology can positively contribute to
perception of potential entrepreneurs that starting a business is achievable. In
addition, such mechanisms promote business start-up to a high social status.
Nevertheless, favourable regulatory mechanisms do not always lead to positive
outcomes. Educator 3, Practitioner 2 and Student 3 suggest that even if the
regulatory support is favourable, not everyone will start a business. Personal
issues such as willingness and readiness to bear risks, prior entrepreneurial
Qualitative Research Findings
184
exposure as well as entrepreneurial and technical skills can all influence business
creation.
Lastly, the current findings resonate with prior research that some nascent
entrepreneurs would not have started their businesses if start-up support was not
available (Gaspar, 2009). Another longitudinal study of 20 necessity micro-
entrepreneurs given short-term loans by an NGO in Mozambique found similar
impact (Tonelli and Dalglish, 2011). In that study, entrepreneurs were required to
participate in mentoring, training and advisory services during the term of the loan.
80% of the business owners improved their businesses after a year’s training while
35% recorded substantial business growth (Tonelli and Dalglish, 2011). Similarly,
the GEM report on 38 countries indicates that a gain in actual business creation
from entrepreneurship training is high “in contexts with favourable institutional
environments” (Martinez et al., 2010, p.6). Therefore, sustained business
development services and mentoring are required to support potential and nascent
entrepreneurs (Sullivan, 2000).
8.1.1.2 Normative Institution’s Influence on EI
A favourable normative institution refers to societal admiration of entrepreneurship,
creativity and innovation. The interviews indicate that such an environment
promotes the entrepreneurial career in a society. It also increases the likelihood of
moral and material support from stakeholders. Below is a quote from Educator 2.
“If starting and managing one’s own business is admired as a high status career in society, many individuals will intend to start a business. This is because it will be seen to be a good and admirable thing in society and that those that endeavour to start are more likely to receive moral and material support from family, friends, peers, colleagues, government and other institutions. I think that support is also more likely to be available if somebody encounters difficulties along the way.” Educator 2
Additionally, the above perspective is clarified by Student 7 that if people in society
admire entrepreneurs, starting a business would be attractive “since individuals
Qualitative Research Findings
185
rarely want to go against the masses”. In assessing the Zambian situation,
interviewees indicate that while admiration for entrepreneurship is increasing, the
majority of those who start businesses are perceived as necessity entrepreneurs
rather than opportunity entrepreneurs (Beeka and Rimmington, 2011; Chigunta,
2002; Kelley et al., 2012).
“In Zambia entrepreneurship is not yet highly admired as a career. But we have started moving in that direction.” Practitioner 3
“…but in Zambia, entrepreneurs who are admired are those who have succeeded. Those who are starting are not admired.” Educator 3
“If starting a business is admired as a high status career option, more people would want to start their own businesses. I have interacted with people in this country, I notice that most people both young and old believe that to succeed in life you need to look for and find a job and not to run your own business. I notice that even some of those who are in business would still want to find a job and run the business in their spare time.” Practitioner 1
“If entrepreneurship is admired as a high status career, more people will consider starting a business. But in Zambia the attitude to entrepreneurship is not favourable. People do not consider it as a career path. It is the last option just for survival.” Educator 1
“If entrepreneurship was perceived to be a high status career, this would be very positive and encourage many people to start business. In Zambia, the perception is that those who start businesses are those who have failed to find a job in the formal sector. So they are viewed as failures. They are viewed as strugglers. This entails that starting one’s own business is the last option.” Educator 2
The interviews suggest that societal admiration of entrepreneurship increases the
likelihood of moral, emotional, regulatory and material support from stakeholders.
Such stakeholders include family, peers, colleagues, media, public and private
institutions. In fact, a favourable normative institution not only positively impacts
subjective norms and social capital but it also influences policy direction.
“If entrepreneurship is admired as a high status choice, more people would intend to start a business because of the perception that it is a good thing and so support from stakeholders will not be difficult.” Educator 3
The empirical evidence suggests that, to improve societal attitudes, there is need
for multifaceted input from the media portraying business role models, from
Qualitative Research Findings
186
community programmes created by enterprise support institutions, and from
schools delivering EE at all levels. This is suggested by Student 6 who observes
that in Zambia, people do not have enough understanding/knowledge of
entrepreneurship as a high status career.
“I think that if we had many successful local business men and women, we would reach a level where starting a business is highly admired as a high status career.” Practitioner 2
“In Zambia entrepreneurship is not yet highly admired as a career. But we have started moving in that direction. We see now that enterprise support practitioners are often invited to churches, schools and other community events to give people first-hand information about business start-up and the support available. People are beginning to realise that for them to survive entrepreneurship should be seen as an answer to some of the challenges they face e.g. unemployment, need for increased household income.”
Practitioner 3
Lastly, all interviewees suggest that the formal education system should provide
the knowledge base and encouragement to promote entrepreneurship. Below are
evidences from the interviews.
“Entrepreneurship training is also important. I know that at school from an early stage in Zambia, we are taught that we should work hard and upon finishing school we should look for a job. This is the way to be successful. So I think that if from an early stage we can be trained that we can be an entrepreneur and start something of our own and still be regarded successful, I think this will be able to change the mind-set.” Student 3
“To change these attitudes, I think we need to start teaching entrepreneurship at primary, secondary through to tertiary levels. We seem to have been brain washed to think that a white collar or blue collar job is more important. This problem is historical. Some other countries have made strides. This is when our country is starting to introduce entrepreneurship at tertiary level but I think it should start at primary level till tertiary. By the time a person reaches tertiary his/her mind-set is already formed and this may be too late. I think now as a country we have realised that the job market cannot take everybody. We have started making efforts but we are still very far in developing this.” Practitioner 2
Overall Observation on the Effect of Normative Institution on EI In summary, a favourable normative institution impacts EI in two ways. Firstly, it
promotes the status of entrepreneurship in society. Secondly, it increases the
likelihood of moral, emotional, regulatory and material support from other
Qualitative Research Findings
187
stakeholders such as family, peers, colleagues, public and private institutions. To
rectify the attitude, a multifaceted input is required from the media, policy makers,
government and non-government enterprise support institutions, as well as
schools.
8.1.1.3 Cognitive Institution’s Influence on EI
A favourable cognitive institution refers to generally shared knowledge and
information in society about how to start and manage a business. The evidence
indicates that it influences EI in two ways. Firstly, it increases people’s
understanding of what is involved in entrepreneurship. Consequently, it influences
potential entrepreneurs’ confidence in their abilities to start and manage a
business. Secondly, it promotes the status of entrepreneurship
“…my view is that, if people know how to start and manage a business and this information is widely shared in society, there will be more individuals believing that they are capable of starting a business. In such an environment, more people will consider starting a business because they know that if they get stuck along the way, they can easily seek help.”
Educator 1
“I think that if people generally know how to register a business, deal with all aspects of business competently, find markets for their products, I think they are more likely to feel confident about starting a business. And if this information is generally shared, there will be perception that starting a business is a good thing.” Student 3
Specifically, the 13 interviews highlight four major benefits that a favourable
cognitive institution can offer. These benefits include shared knowledge about how
to start, manage and grow a business (13); how to legally register and protect a
business (13); how to identify and manage risks (13); and, how to identify and
serve markets (13). In addition, it would increase potential entrepreneurs’
confidence in starting and managing a venture. From their experiences,
Practitioners 2 and 3 indicate that individuals with and without EI are distinguished
in three aspects: knowledge about business; educational level; and,
Qualitative Research Findings
188
entrepreneurial skills. These aspects also determine the success rate of nascent
entrepreneurs, a view that resonates with prior research (Martínez et al., 2010;
Robinson and Sexton, 1994).
Furthermore, the evidence suggests that besides formal education processes,
other mechanisms for diffusing entrepreneurship knowledge/information include
media, community programmes and enterprise support institutions. When these
are widely spread across a country, they help promote entrepreneurship.
“…In Zambia, people mostly do not know how to start, operate and grow a business. They do not know where to find markets and other relevant information. The few relevant institutions like the PACRA (Patents and companies Registration Agency), ZDA (Zambia Development Agency) and the CEEC (Citizens Economic Empowerment Commission) are too centralised for information to be accessed easily by many citizens.”
Student 1
“…In Zambia, people generally do not have knowledge and information about how to start and grow a business, where to find markets, and so on. Those who have information do not want to share. Most start-ups have a problem of finding information needed to conduct business idea evaluation. In other countries, information from government, government institutions and other institutions generating various statistics is available on websites for ease of access as input when one is conducting a feasibility study. In Zambia, those who have information want to charge for it. Private business development service providers charge unaffordable fees for their services, for example, coaching and training on how to register a business and how to develop a business plan.” Educator 1
“Shared information about entrepreneurship will lead to attitudes that are favourable to entrepreneurship. Shared information will also result in would-be entrepreneurs believing that starting a business is viable. ” Educator 3
“I think that if we had many successful local business men and women, we would reach a level where starting a business is admired as a high status career. I think now as a country we have realised that the job market cannot take everybody. Successful businessmen are starting to be acclaimed by the media and schools such that they are now often called to share their experiences in schools and in the media. We have started making efforts but we are still very far in developing this.” Practitioner 2
“The awareness is also being delivered through community and media programmes. So those who are paying attention to what is happening in the environment may get to know about available support.” Practitioner 3
Qualitative Research Findings
189
Overall Observation on the Effect of Cognitive Institution on EI A favourable cognitive institution increases people’s understanding of what is
involved in entrepreneurship. Consequently, it influences potential entrepreneurs’
confidence in their abilities to start and manage a business. Additionally, it
promotes the status of entrepreneurship. Lastly, all stakeholders such as
government, entrepreneurs, support institutions, students, educators and the
media should be involved in promoting entrepreneurship. This view also echoes
extant literature (Matlay, 2009).
8.1.1.4 Summary of Effects of Institutional Factors on EI
The empirical evidence has shown that regulatory, cognitive and normative
institutions have an effect on entrepreneurship cognition and behaviour.
Specifically, these institutional factors have an influence on EI through perceptions
that business start-up is not only possible but also worthwhile. Besides the
regulatory, normative and cognitive institutions, perceived difficulties in the labour
market may compel some people to the entrepreneurship trajectory (Beeka and
Rimmington, 2011; Kelley et al., 2012). However, Practitioners 2 and 3 and all the
educators and students interviewed observe that while business start-up may be
one of the options in the quest for livelihood, it may not be feasible. Consequently,
the influence of low job prospects is limited. This is because it may not necessarily
lead to EI or successful start-up if perception of feasibility is absent. The
implication is that although lack of job opportunities may be a trigger, other factors
that affect feasibility and desirable are more important, a view that is consistent
with prior research (Byabashaija and Katono, 2011; Dohse and Walter, 2012;
Shapero and Sokol, 1982).
Lastly, prior research conceptualised and investigated institutional factors’ effect
on entrepreneurship based on macro level variables (Bruton et al., 2010).
Qualitative Research Findings
190
Empirical evidence in the current study has contributed to filling the knowledge
gap by examining the influence of institutional factors on micro variables i.e.
individual cognition (Bruton et al., 2010, Wicks, 2001; De Clercq et al., 2011).
8.1.2 Individual and Background Factors’ Influence on EI
Prior research indicates that individuals choose careers/jobs that match their
personalities, needs and interests (Holland, 1959; Holland, 1997; Judge and
Kristof-Brown, 2004; Kristof‐Brown et al., 2005; Rauch, 2007; Zhao and Seibert,
2006).This is because individuals differ in ability, temperament, speed and style of
learning. Thus, facing the same information, skills, opportunities or costs, some
individuals will decide to exploit an entrepreneurial opportunity while others will not
(Shane, 2003). This means that these individuals may have a combination of
psychological characteristics which, in interaction with other background and
contextual factors, make them more likely to attempt to found a business (Frank et
al., 2007; Gnyawali and Fogel, 1994; Krueger and Brazeal, 1994; Learned, 1992).
Founding and managing a business requires that an entrepreneur plays a number
of unique roles. For instance, such roles include innovator, risk taker and bearer,
manager, relationship builder, risk reducer and goal achiever (Chen et al., 1998).
The implication is that individuals are attracted to entrepreneurship because of a
self-perceived match between their characteristics and the demands of
entrepreneurship (Dyer, 1994; Frank et al., 2007; Rauch and Frese, 2007; Zhao et
al., 2005).
Consistent with the theoretical perspectives above, the interviews indicate that
individuals are different and those with characteristics and backgrounds aligned to
the requirements of entrepreneurial tasks and activities are more likely to start a
business. Below are two quotes from the interviews.
Qualitative Research Findings
191
“…from my experience in interacting with entrepreneurs that come to our institution to access various support facilities, I have observed prominent personal characteristics among these entrepreneurs; the characteristics include risk taking tendency, appetite to achieve something and the desire to be independent in life…the desire and belief to determine their own destinies and future…wanting to be one‘s own boss…such people believe in their own abilities and are attracted to the rewards of business.”
Practitioner 3
“…for individuals who are starting businesses in this country, there are many reasons at play…having a background of running a business or a family business is one of them; for example, if one has inherited a business or one is a prior founder, entrepreneur or it could be the trend in the family where the entrepreneurial spirit is drawn from. Such people are attracted to the life of an entrepreneur because they not only consider it a good thing but they also feel more capable of doing it because they have seen it before.” Educator 2
Specifically, the 13 interviews identified major individual and background factors
relevant to entrepreneurship. These factors include internal locus of control (13),
need for achievement (12), risk taking propensity (13), and prior entrepreneurial
exposure (7).
8.1.2.1 Locus of Control’s Influence on EI
The interviews indicate that individuals who believe that through effort they can
achieve their goals are more likely to start a business. Such individuals have an
internal locus of control (ILC). Below are quotes from the interviews, including one
from Student 2 who is already an entrepreneur and intends to grow her business.
“I believe that as an individual I determine my own destiny and any external obstacles such as not having support from others can be overcome. Having my own business gives me an opportunity to have the lifestyle I want.” Student 2 “those who believe that they are in control of their destinies are more likely to attempt to go into business but those who focus on obstacles and external challenges may not attempt let alone succeed because they easily give up.” Educator 2
“Individuals who think they are masters of their own destiny, who believe that if they work hard they will be able to achieve their own goals, are likely to be entrepreneurs. Individuals who are unlikely to be entrepreneurs are those who resign themselves to fate i.e. the view that whether one succeeds or not was meant to be that way…masters of their own destiny
Qualitative Research Findings
192
are likely to believe that going into business is a good thing for them as it would enable them achieve their goals .” Educator 3
From the foregoing, individuals with high ILC are more likely to start a business.
This is because starting a business requires a high degree of belief in one’s
abilities to influence outcomes. In addition, such individuals find starting a
business attractive because it provides a direct link between effort and one’s
desired outcomes. This view is consistent with prior research that individuals with
high ILC believe that their own efforts determine whether or not they achieve their
goals (Judge et al., 2002; Rotter, 1966). Unlike individuals with an external locus
of control, such individuals underplay the influence of luck, fate and obstacles in
the environment. Prior research further indicates that an individual’s belief about
the value of entrepreneurial opportunities depends partly on his/her own
evaluation of his/her abilities to exploit those opportunities. This evaluation in turn
depends on the degree to which the individual believes he/she can influence
outcomes. Thus, an individual with higher ILC is more likely to have higher EI
(Lüthje and Franke, 2003; Rauch, 2007; Verheul et al., 2012).
8.1.2.2 Need for Achievement’s Influence on EI
The interviews indicate that individuals with higher need for achievement (NAch)
are more likely to start a business. Below are quotes from Student 2 who explains
the decisions she had to make in starting her business as well as Practitioners 2
and 3 who cite their experiences with entrepreneurs.
“…(Worked for… years in a government department)…I did not like the work culture and I wanted to achieve something meaningful on my own. So I quit and decided to start a retail business dealing in…I was running the business with the assistance of…but I had no business management skills. I encountered problems with managing cash flow and I did not know how to expand the business. To improve my skills, I decided to study for the…to equip me with marketing skills. But this did not help me with managing cash flow and how to competently handle other aspects of the business. So three years into running my own business, I decided to sponsor myself to study this…(while remotely supervising staff and checking on them in person on a…basis so that the business is running smoothly).” Student 2
Qualitative Research Findings
193
“…for them (entrepreneurs) to have even been comfortable to pledge their only house as collateral I think apart from being risk taking, they believe in their own abilities to influence their success. These people’s dedication to achieve growth in their business is evidenced from the collateral they pledged… Another interesting observation is that some people that come together to work as a cooperative or as friends to do business together are among those not successful and they blame a lot of external factors for failure…the fighting spirit does not seem to be there among those who fail. Those who succeed seem to exhibit a fighting spirit in spite of obstacles.” Practitioner 1
“an appetite to achieve something meaningful in one’s life and to be independent in life leads one to consider starting a business. We see this in individuals who say they are tired of working for somebody else; Instead of working every day for somebody else, they think that they should do this for themselves and achieve something meaningful for themselves…it is not surprising that such people find business attractive and believe that they can succeed despite the obstacles”. Practitioner 3
The interviews indicate that individuals who are ambitious and believe that
success depends on their own efforts are more likely to start a business. This
finding resonates with prior research that individuals with higher NAch are more
likely to have EI (Brockhaus and Horwitz, 1986; Frank et al., 2007) and
subsequently engage in entrepreneurship (Frank et al., 2007; Rauch and Frese,
2007). Extant literature construes NAch as an individual’s persistence, hard work
and motivation for significant accomplishment. It is the most consistent personality
predictor of job performance across all types of work and occupations (Zhao and
Seibert, 2006). NAch drives an individual to seek careers and tasks in which
performance is due to one’s own efforts and not the efforts of others (McClelland,
1965). No wonder individuals with a high NAch are more likely to choose to
engage in entrepreneurship.
8.1.2.3 Risk Taking Propensity’s Influence on EI
The interviews indicate that individuals with high risk taking propensity (RTP) are
more likely to start a business. For instance, Educator 3, Student 7, Practitioners 2
Qualitative Research Findings
194
and 3 observe that generally individuals who are open to new ideas and are
comfortable dealing with risk and situations of uncertainty are likely to find
entrepreneurship attractive and viable.
“I have seen from my experience that for entrepreneurs to be comfortable even to pledge their only house as collateral, I think they are not only taking risk but they also believe in their abilities to influence the outcomes of the businesses they start…needless to say, they are attracted to business.” Practitioner 1 “I know that individuals who are generally comfortable dealing with uncertainty and risk feel capable of handling the uncertainties of starting and managing a business. They find entrepreneurship to be exciting and attractive. Such individuals have higher odds of starting a business.” Educator 3 “Business offers no certainties. Businessmen and women invest money today and hope that in the near future they will get a return. The entrepreneurs I have dealt with are individuals who are generally open to new ideas and are ready and feel capable of dealing with uncertainty. So entrepreneurs are risk takers. They take risk because they are excited about the potential rewards. So I think people who don’t fear uncertainty will be attracted to start a business and they will consider it doable despite the uncertainties it brings.” Practitioner 3
RTP connotes the tendency for an individual to embrace or shun tasks and
situations that involve uncertainty (Segal et al., 2005). This means that some
individuals, more than others, would be eager to start something new or engage in
an activity even if they have no guarantee as to whether it will succeed or not. The
founder of a business commits resources to an activity that may or may not yield
positive results. Therefore, business start-up is fraught with uncertainty. No
wonder individuals with higher RTP are more likely to engage in entrepreneurship
(Frank et al., 2007; Lüthje and Franke, 2003; Zhao et al., 2005).
8.1.2.4 Prior Entrepreneurial Exposure’s Influence on EI
In addition to the major individual characteristics discussed above from
subsections 8.1.2.1 to 8.1.2.3, the interviews indicate that individual background
influences EI. The major background factor identified is prior entrepreneurial
Qualitative Research Findings
195
exposure (PEE). The evidence suggests that individuals with PEE are more likely
to find entrepreneurship attractive. They are also more likely to have confidence in
their abilities to start and manage a business. Below is a quote from the interview
with Practitioner 3.
“We have also seen that for some people, they find entrepreneurship attractive and achievable if they have closely seen or worked with a successful role model who could be a neighbour, friend or family. In this way, they also become motivated to consider starting a business. Such individuals believe that starting and managing a business is possible because they have seen it done before and also because they think they know where to get help if needed.” Practitioner 3
Consistent with the above perspective, Practitioner 1 recalls dealing with
entrepreneurs who already had existing businesses when they sought further
funding for expansion or to start another business. These were either owner
managers or individuals running family businesses. Educator 2 and Student 4
indicate that individuals who have either founded a business before or have family
members as entrepreneurs are more likely to engage in entrepreneurship. This is
because such individuals are exposed to entrepreneurship. Consequently, they
have higher confidence that they can start a business and that it is a desirable
undertaking. This view is consistent with prior research (BarNir et al., 2011; Carr
and Sequeira, 2007; Krueger, 1993).
8.2. The Intervening Role of EE on Effects of Factors Influencing EI
The preceding section has discussed the evidence on what, how and why
institutional and individual factors influence EI. This section discusses how
entrepreneurship education (EE) affects the relationships between institutional
factors and EI as well as the relationships between individual factors and EI.
8.2.1 EE Intervening in the Effects of Institutional Factors on EI
The interviews indicate that the effects of the entrepreneurial environment on EI
are mediated by the level of entrepreneurship knowledge and skills acquired
Qualitative Research Findings
196
through EE i.e. effectiveness of EE. This is because individuals learn how to start
and manage a business within a specific environmental context. In other words, a
favourable entrepreneurial environment makes people realise the value and
importance of entrepreneurship and enhances the perception that it is achievable.
This realisation affects interest, attitude and zeal in EE. Thus, institutional factors
affect the effectiveness of EE. This in turn influences perception that business
start-up is both possible and worthwhile. Below are three quotes from the
interviews.
“I think that entrepreneurship education enables individuals to understand their environment better and how that environment would influence success or failure for a prospective start-up. Therefore, students become more aware of the support or lack of support in the environment from various stakeholders. However, the environment affects the extent to which they believe entrepreneurship is important and worthwhile. For me this perception affects interest and intensity of involvement in the entrepreneurship module. Ultimately, this affects the extent which one learns how to start and manage a business and the extent to which they believe that entrepreneurship is worthwhile. In the end, I think it will affect the business start-up decision.” Educator 2
“Training helps individuals become more aware of their environment from a business point of view. It also highlights how to identify the opportunities and support in the environment and how to benefit from the available support. But unsupportive environment affects the level of interest and effort in the training. Now if the environment is unsupportive, it will adversely affect how the individual applies himself/herself during the training and this would affect the extent to which the individual thinks that he/she has learnt how to start and manage a business through the training. It will also affect the thinking about whether business start-up is worth it and possible. So for me, it is clear that we need to improve the support in the environment and offer training for us to promote entrepreneurship.” Practitioner 2
“…the course has given me an opportunity to learn about and interact with specific sources of support and how to access that support… Of course, there are many challenges in the environment for business start-ups but we have learnt some alternatives/options to try and deal with those.” Student 5
Extant literature indicates that perceived business environment influences new
business creation (Zahra, 1993; Zahra and Covin, 1995; Souitaris et al., 2007).
Based on reviews of extant literature, scholars indicate the need to explore if, why
and how EE and its impact differ in different learning contexts and with different
Qualitative Research Findings
197
individuals (Rideout and Gray, 2013; Wang and Hugh, 2014). These interviews
clarify that institutions will drive people to EE. This means that favourable
institutions will make people realise the value and importance of entrepreneurship
and this would impact their interest, attitude, and effort toward EE, ultimately
affecting the effectiveness of EE. EE not only helps develop knowledge and skills
but also clarifies the benefits of entrepreneurship. The effectiveness of EE would
then influence perceptions that entrepreneurship is valuable and viable. Thus, the
effect of the entrepreneurial environment on EI is mediated by level of knowledge
of entrepreneurship achieved through EE. In other words, the environment has an
influence on the effectiveness of EE. This in turn influences perception that
business start-up is possible and worthwhile.
The evidence also indicates that, given the same entrepreneurial environment, EE
participants would perceive the same environment more favourably than non-
participants. This is because, during EE, participants have opportunities to assess
various aspects of the entrepreneurial environment. Thus, they gain understanding
of the environment’s effect on a potential start-up. They also consider how to
mitigate challenges in the environment. This view echoes perspectives in extant
literature that, although it is difficult to prepare fully for the challenges of
entrepreneurship, some prospective entrepreneurs are more prepared than others.
This underscores the importance of prior knowledge, training and experiences
(Cope, 2005; Gibb and Ritchie, 1982).
8.2.1.1 EE Intervening in the Effect of Regulatory Institution on EI
The interviews establish that the regulatory institution affects the effectiveness of
EE. Specifically, individuals who think that the regulatory institution is conducive to
business start-up are more likely to be interested and motivated to acquire
entrepreneurship knowledge and skills through EE. Knowledge of
Qualitative Research Findings
198
entrepreneurship will in turn affect the thinking that business start-up is possible
and worthwhile. Below are two quotes from the interviews.
“…business development and advisory services from government and other institutions for SMEs are important. They re-assure me that help is available if I need it along the way when I start my business…availability of such support affects enthusiasm and effort with which one responds to entrepreneurship training…this affects the training…So my confidence in whether I have learnt enough to start a business will be affected by the perception about whether the environment is supportive.” Student 5
“Available support currently includes access to capital from CEEC and microfinance institutions though the latter prefer dealing with salaried employees. But most, if not all, available debt finance requires collateral. So it is not easy for someone who cannot meet these conditions, especially us young ones at the start of our careers. There are no specific places where one can go for business advisory services in Zambia…. Because of such challenges, many of my fellow students have low interest in becoming an entrepeneur and in entrepreneurship training...So even if I receive training on how to start and run a business, the extent to which I think I have acquired enough knowledge and skills to successfully start a business is hampered by these challenges in the environment.” Student 6
Moreover, EE exposes individuals to the techniques, tools and processes of how
to start and manage a business. It also provides an opportunity to learn what the
regulatory environment requires. Thus, participants in EE understand the
regulations better. They also understand how to access the available support.
Below are quotes from the interviews.
“…because of my participation in EE, I have known the players in enterprise support and what I need to do to access the support from these institutions…also I think that the fact that some level of support is available for start-ups means that entrepreneurship is considered important in this country.” Student 7
“While the argument from my parents is that I should not start a business because start-up capital is a challenge, I have learnt that not all businesses require huge amounts of capital to start with. In addition, through networking I can raise the necessary capital or work with partners. For example in my case, the past few months with my colleagues we have been undertaking consultancy services to upcoming entrepreneurs and SMEs on how to prepare business plans from which we have managed to raise some money we will use to start a…business. So it has broadened and deepened my options on how to start a business.” Student 4
Qualitative Research Findings
199
Furthermore, as illustrated by Student 4, the interviews indicate that EE helps
participants to consider and develop alternatives to mitigate challenges. Overall, it
is clear that perceived conduciveness of the regulatory institution affects
confidence in the level of knowledge and skills acquired through EE. This in turn
affects perceived feasibility and desirability of entrepreneurship.
8.2.1.2 EE Intervening in the Effect of Normative Institution on EI
The interviews show that societal admiration of entrepreneurship affects
individuals’ attitudes to entrepreneurship learning. This means that the attitude to
entrepreneurship affects effort, zeal as well as actual and perceived performance
in EE. Perceived effectiveness of EE will in turn influence the thinking that
business start-up is possible and worthwhile. Below are quotes from the
interviews.
“I think that the general attitude in society and from the school system from an early stage in Zambia is that one should work hard and upon completion of school look for a well-paying Job… this is the way to be successful in life. So I think that if society highly admired entrepreneurs and if we were also pointed to the option of starting and managing one’s own business from an early stage in life, this would change the mind-set and attitude with which one enters entrepreneurship training. This in turn affects learning… achievements and ultimately the belief that one is able to start something and whether it is worth it. For example, we have some of our colleagues who are not taking the module who ridicule us that we are wasting our time because self-employment is for those who are stranded and can’t get a job elsewhere.” Student 6
“The training has helped me learn to deal with negative attitudes about entrepreneurship from others. Despite negative attitudes you learn to be decisive and not procrastinate since you understand what needs to be done. In fact, I know that the same people who criticise me will begin to admire me once I succeed. This is because, in our society, successful entrepreneurs are admired. But those who are starting and those who have failed are not admired…but this is not to diminish the fact that society’s attitude affects me as a student in terms of my attitude toward training. I must admit this ultimately negatively affects learning, my confidence in my abilities to start something and the conviction that I am doing the right thing for myself.” Student 3
Moreover, the evidence suggests that EE participants are likely to be more
assertive in dealing with negative attitudes from society about entrepreneurship.
Qualitative Research Findings
200
This is because they develop an understanding of what is involved in
entrepreneurship as well as its benefits. In summary, it is clear that the normative
institution influences attitudes, zeal and effort in entrepreneurship education,
thereby impacting its effectiveness. Effectiveness of EE in turn influences the
perception of feasibility and desirability of entrepreneurship. Ultimately perceived
desirability and feasibility of entrepreneurship determine EI.
8.2.1.3 EE Intervening in the Effect of Cognitive Institution on EI
The interviews indicate that generally shared information in society about
entrepreneurship influences the effectiveness of learning. This learning in turn
influences the perception that entrepreneurship is possible and that it is valuable.
Below are three quotes from the interviews.
“I think that if information about how to start and manage business is rarely shared in society and if the level of understanding about entrepreneurship is generally low in society, this would negatively affect entrepreneurship training… because participants enter with low levels of understanding about entrepreneurship and its benefits. So they are less interested in what they are learning. I think this affects the outcome of the training as well as the confidence that one is able to successfully venture.” Practitioner 1
“…we have overemphasised the value of getting paid employment in existing organisations i.e. getting a white collar or blue collar job rather than being self-employed and so information about starting and running business is not generally shared…; I think we should have started sharing this information much earlier through primary and secondary schools, the media and in the community. By the time a person reaches tertiary education, his/her mind is already set and this may be too late…as it detracts from the effect of entrepreneurship training… I think it affects the attitude and interest in business start-up and the training itself…and this would affect the thinking that one is capable of becoming an entrepreneur and that it is worthwhile.” Practitioner 2
“I think that exposing an individual to entrepreneurship education would deepen understanding of what is involved and the benefits…So the effect of education should be positive though not as much as it would be if society shared that information and knowledge widely. This ultimately affects whether one values entrepreneurship and feels capable of doing it.” Practitioner 3
Further to the perspectives in the quotes above, Educator 1 suggests that EE not
only clarifies the benefits of entrepreneurship but also provides specific, accurate
Qualitative Research Findings
201
knowledge about how to start and manage a business. However, if the level of
knowledge and information shared about entrepreneurship in society is low, this
affects the level of interest in EE and, therefore, the extent to which participants
learn how to successfully start a business. This means that shared
entrepreneurship knowledge and information in society affects the extent to which
students believe entrepreneurship is important and this influences effort, interest
and the consequent performance in EE. Therefore, it is clear that conduciveness
of the cognitive institution influences effectiveness of EE. Effectiveness of EE in
turn affects perceptions of feasibility and desirability of entrepreneurship.
8.2.2 EE Intervening in the Effects of Individual Factors on EI
The interviews indicate that EE not only clarifies the benefits of entrepreneurship
but also develops capacity in terms of entrepreneurship knowledge and skills.
However, EE participants differ in ability, temperament, personality, interests and
upbringing/socialisation. Some characteristics on which individuals differ
determine whether one considers the tasks, roles and activities of
entrepreneurship attractive and manageable. Individuals with characteristics
required for entrepreneurship have favourable attitudes to entrepreneurship and,
therefore, EE. This favourable predisposition affects effort and performance in EE.
This in turn leads to higher perceptions that business start-up is not only possible
but also worthwhile. Below are quotes from the interviews.
“Individuals with relevant characteristics have higher odds of starting a business and achieving higher learning outcomes on how to run a business. This is because they already find it attractive to engage in such activities and so they apply themselves more during the training.” Student 4
“…Individuals with characteristics appropriate for entrepreneurship are more likely to do better in entrepreneurship training. This is because they are more excited about the prospect of starting a business and so more eager to learn how to do it successfully…because they learn more and faster, they feel more capable.” Student 5
Qualitative Research Findings
202
“For individuals who receive entrepreneurship training, the level of confidence in abilities to start a business is enhanced because of the knowledge, tools and techniques they acquire. That said, we should remember that two individuals can be taught how to build a house but one may actually decide to build and the other may decide not to build. Moreover, even if they both decide to build, the size and type of house may differ. So the individual factors will still have some effect both on entrepreneurship and the learning outcomes…this will reflect in differences in abilities and attraction to self-employment.” Educator 3
The preceding perspectives are consistent with extant literature that attitude and
interest toward a subject influence effort in learning and consequent performance
(Blickle, 1996; Chamorro‐Premuzic and Furnham, 2003; De Fruyt and Mervielde,
1996; Lewis et al., 2009; Lievens et al., 2002; Matlay, 2010). Therefore, individual
factors relevant to entrepreneurship would influence the effectiveness of EE. This
is because individuals with relevant characteristics are more attracted to
entrepreneurship and, therefore, are more eager to learn how to become
successful entrepreneurs. Effectiveness of EE in turn influences perceptions of
feasibility and desirability of entrepreneurship.
8.2.2.1 EE Intervening in the Effect of Risk Taking Propensity on EI
Risk taking propensity (RTP) is willingness and readiness to bear uncertainty
(Ahmed, 1985). The interviews indicate that RTP influences effectiveness of EE.
This is because entrepreneurship requires managing uncertainty and so
individuals with high RTP are more receptive to learn about entrepreneurship.
Consequently, the difference in attitude, effort and zeal would affect performance
in EE. EE clarifies the benefits of entrepreneurship and helps build capacity to
engage in business start-up. Therefore, effectiveness of EE in turn influences
perceived feasibility and desirability of entrepreneurship. This is clear in the case
of Student 2 who had already voluntarily resigned from organisational employment
to start a business. After she realised she did not have enough skills to handle
Qualitative Research Findings
203
certain aspects of the business, she decided to pursue EE. At the end of the
course she declares:
“Speaking from my experience, I can say that I have been transformed during these four years in entrepreneurship education. I now have confidence to take on bigger challenges. I am now able to grow my business. I am now more creative and can follow through the process of innovation. I can identify, evaluate, reduce and manage higher risks in a business. I can manage finance and handle human resources issues…At the end of a mandatory internship in third year, I was at the… and was offered a job but I declined because my priority now is to grow my business.” Student 2
“Individuals who are ready and willing to deal with uncertainty are attracted to entrepreneurship. Such individuals are also more interested in entrepreneurship training because they want to learn how to engage in entrepreneurship succesfully. Therefore, they would benefit more from such training because of their interest.” Practitioner 3
The evidence clearly shows that RTP influences the level of knowledge of
entrepreneurship acquired through EE. Entrepreneurship knowledge and skills in
turn influence perceived feasibility and desirability of entrepreneurship.
8.2.2.2 EE Intervening in the Effect of Internal Locus of Control on EI
An individual with an internal locus of control (ILC) believes that through effort and
capability one can achieve his or her goals (Ahmed, 1985; Rotter, 1966). Faced
with challenges and obstacles, such individuals have a tendency to persevere.
They are also attracted to activities that show a direct link between effort and
outcome.The interviews indicate that ILC influences effectiveness of EE. This is
because individuals with higher ILC enter EE with higher confidence in ability to
perform in education and in the challenging tasks of entrepreneurship. They are
attracted to entrepreneurship because it provides a direct link between effort and
rewards. Generally, such individuals already possess higher self-belief to succeed.
Consequently, they would report higher perceptions of learning in EE. Below is a
quote from the interviews.
Qualitative Research Findings
204
“I think that individuals who are naturally confident in their ability to achieve anything are attracted to entrepreneurship because it requires a person to believe in his or her own efforts and abilities to achieve results. Such individuals are likely to have a more positive attitude to learning the challenging tasks of starting and managing a business…understanding of entrepreneurship will bring about a conviction that starting a business is achievable and that it is a good thing… So I think such individuals will have an advantage in learning entrepreneurship.” Student 5
The forgoing perspective is clarified by Student 2 that she believes that as an
individual she determines her own destiny and any external obstacles can be
overcome. She acknowledges that EE has transformed her to the extent that she
now believes she has more capacity to grow the business she already owns. This
view resonates with prior research that entrepreneurs have higher ILC than non-
entrepreneurs (Mueller and Thomas, 2001; Ahmed, 1985). This means that
entrepreneurs believe that the outcome of a business venture is mainly
determined by their own efforts.
Overall, it is clear that Individuals with high ILC have higher perception of
knowledge and skills acquired through EE. The reasons for this are twofold.
Firstly, entrepreneurship requires belief in one’s abilities and efforts to achieve
desired outcomes. Such individuals already have this belief and EE helps develop
it further. Secondly, such individuals are learning to perform tasks that they
already find challenging and attractive. Hence, they are more eager to learn how
to be successful entrepreneurs. Effectiveness of EE in turn influences perception
that entrepreneurship is not only possible but also worthwhile.
8.2.2.3 EE Intervening in the Effect of Need for Achievement on EI
Need for achievement (NAch) is based on the expectation of doing something
better than others or better than one’s earlier accomplishments (Ahmed, 1985;
McClelland, 1967). The interviews indicate that NAch affects the effectiveness of
EE. This is because individuals with high NAch are attracted to the tasks/activities
that pose a high challenge yet achievable. They are also attracted to activities that
Qualitative Research Findings
205
provide a direct link between one’s effort and meaningful accomplishments.
Business start-up is one such activity. Therefore, individuals with a high NAch
report higher learning achievement in EE because they have a favourable attitude
to learning about how to be successful entrepreneurs.
“Individuals with a high need to achieve something meaningful in life have higher odds of doing better in the course on entrepreneurship. I say so because entrepreneurship gives them something that can distinguish them from others and so they are excited about it already. Such individuals will apply themselves more in the learning process and this will lead to higher performance. So they will feel more capable about starting something.”
Educator 2
Overall, it is clear that individuals with high NAch are more likely to report higher
effectiveness of EE. This is because they are learning how to perform tasks that
they find attractive. Knowledge of entrepreneurship acquired through EE
influences perception that business start-up is both possible and valuable.
8.2.2.4 EE Intervening in the Effect of Prior Entrepreneurial Exposure on EI
The interviews indicate that the breadth and positiveness of prior entrepreneurial
exposure (PEE) affects not only one’s desire to engage in entrepreneurship but
also the belief that it is achievable. The evidence also shows that PEE affects the
effectiveness of EE. This means that individuals with PEE already find
entrepreneurship attractive. Therefore, they enter the process of EE with a
favourable attitude to learn more about how to be successful entrepreneurs. Below
are quotes from the interviews.
“We have also seen that for some people, they find entrepreneurship attractive and achievable if they have closely seen or worked with a successful role model who could be a neighbour, friend or family. In this way they also become motivated to consider starting a business… Therefore, such individuals enter entrepreneurship training eager to learn more about how to become successful at what they already like. So I think they have an advantage over those who do not have such exposure… More understanding should result in more confidence that they can do it and that it is the best thing for them…” Practitioner 3
Qualitative Research Findings
206
“Speaking from my experience, I came here already owning a business but I wanted to learn more so that I can have capacity to grow my business. I can say that I have been transformed during these four years in entrepreneurship education. I now have confidence to take on bigger challenges. I am now able to grow my business. I am now more creative and can follow through the process of innovation. I can identify, evaluate and manage higher risks in a business. I can manage finance and handle human resources issues…At the end of a mandatory internship in third year, I was at the... and was offered a job but I declined because I want to grow my business.” Student 2
“Once they go through entrepreneurship training they see the benefits of being an entrepreneur and acquire the knowledge, skills and techniques to successfully engage in business start-up.” Practitioner 1
The foregoing evidence suggests that EE not only clarifies the benefits of
entrepreneurship but also helps develop capacity to successfully engage in
business start-up and growth. However, PEE affects attitude, zeal and effort in EE.
Peterman and Kennedy (2003) find that individuals with PEE are more likely to
choose to participate in EE. This means that the level of interest in EE differs
depending on the indvidual. This would result in differences in the effectiveness of
EE. Therefore, the evidence clarifies that PEE influences the level of
entrepreneurship knowledge and skills acquired through EE. This in turn further
influences perceptions that business start-up is not only possible but also valuable.
8.3 Implications of Findings to the Conceptual Model
The preceding empirical evidence indicates that institutional factors and individual
factors positively influence EI. In addition, as indicated in Figure 8.1, EE mediates
the relationships between EI and its institutional and individual determinants. This
means that both individual and institutional factors have an influence on an
individual’s perceived and actual effectiveness of EE. Effectiveness of EE in turn
influences EI through the perceived feasibility and desirability of entrepreneurship.
Qualitative Research Findings
207
Figure 8.112- Overview of Qualitative Research Findings on Determinants of EI
Based on the literature review, the conceptual model (Figure 6.2 in chapter 6
section 6.1) was developed to guide enquiry on factors influencing EI and the role
of EE. The conceptual model was the basis for conducting qualitative research
through interviews with practitioners in entrepreneurship support institutions,
educators and final year university students participating in EE in Zambia. Based
Qualitative Research Findings
208
on the qualitative research results discussed in this chapter, the proposed
conceptual model is supported. The conceptual model is also tested through
quantitative research which involved a survey of final year university students in
Zambia. The results of the survey are discussed in chapter 9.
8.4 Conclusions
This chapter has discussed the qualitative research results based on 13 interviews
with practitioners in entrepreneurship support institutions, educators and final year
undergraduate students involved in EE in Zambia. The results have been
discussed in the context of extant literature on factors influencing EI. In a nutshell,
the conclusions are twofold:
Firstly, individual and institutional factors influence EI via perceived feasibility and
desirability of entrepreneurship. Specific elements of the individual and institutional
factors are involved. With respect to individual factors, major influences include
need for achievement, risk taking propensity, locus of control and prior
entrepreneurial exposure. These influence perception that entrepreneurship is a
valuable undertaking and that it is possible. The major institutional factors include
the normative, cognitive and regulatory institutions. While perception of low job
prospects in the labour market may lead an individual to consider starting a
business, the evidence suggests that its influence is limited. This is because it may
not necessarily lead to EI or successful start-up if perceived feasibility is low. This
means that although lack of job opportunities may be a trigger, other factors that
affect feasibility and desirability may be more important. These findings show how
institutions affect individuals’ cognition and EI; institutions influence perception that
business start-up is worthwhile and viable. Hitherto institutions have been
Qualitative Research Findings
209
conceptualised and investigated as determinants of entrepreneurial activity at
macro level (Bruton et al., 2010; Wicks, 2001; De Clerq et al., 2011).
Secondly, EE has an intervening role in the relationships between EI and its
individual and institutional determinants. This entails that individual and
institutional factors influence effectiveness of EE i.e. level of entrepreneurship
knowledge and skills acquired through EE. Effectiveness of EE in turn influences
EI through perceived feasibility and desirability. This means that institutions drive
people to EE; institutions make people realise the importance of entrepreneurship
and this leads to interest, favourable attitude, and effort toward EE. This affects
the effectiveness of EE. Effectiveness of EE then affects feasibility and
desirabaility perceptions. Individual factors also influence zeal, effort and
receptiveness toward entrepreneurship and EE. This affects the effectiveness of
EE which in turn influences EI via perceived feasibility and desirability. Lastly,
some scholars suggest that EE and its impact may differ in different learning
contexts and with different individuals (Cope, 2005; Wang and Hugh, 2014;
Rideout and Gray, 2013). Moreover, De Clercq et al. (2011) recommend that
future studies should investigate combinations of individual and institutional
factors’ influence on perceived feasibility to start a business. However, hitherto, no
empricial study has developed, tested and validated a conceptual model to reflect
these suggestions. Clearly, the results in this study have shown that individual and
institutional factors are the primary predictors of EI. The role of EE is to provide
additional avenue/mechanism for individual and institutional factors to influence EI.
The next chapter discusses the quantitative research results.
210
CHAPTER 9: QUANTITATIVE RESEARCH FINDINGS
9.0 Introduction
The preceding chapter discusses the qualitative research findings. This chapter
reports and discusses results of quantitative testing of the conceptual model. The
results are based on the survey data from 452 final year students participating in
entrepreneurship education (EE) in Zambia. Additionally, the results are
interpreted and discussed in the context of findings from qualitative research and
prior research. Following validity and reliability analyses of quantitative measures
in Chapter 7, the score on each dependent, independent and intervening variable
for each respondent was obtained by averaging the score of the retained items.
However, for prior entrepreneurial exposure, the score was the average of the 5-
point Likert scales and dichotomous scales.
Section 9.1 highlights inter-correlations among all the variables. Section 9.2
discusses multiple regression tests of the entrepreneurial intention (EI) model.
Section 9.3 highlights regression-based mediation analyses guidelines in the
extant literature. Section 9.4 discusses the tests of EE mediating the effects of
individual and institutional factors on perceived feasibility and desirability of
entrepreneurship. The overall conclusion is that indeed EE has an intervening role.
Specifically, it mediates the effects of individual and institutional factors on
perceived feasibility and desirability of entrepreneurship. Perceptions of feasibility
and desirability then determine EI.
9.1 Correlation Analyses among all Variables
The Table 9.1a reports the means and standard deviations of dependent,
independent, mediating and control variables. The correlations among the
Survey Research Findings
211
variables are also presented. Relatively low inter-correlations among variables
indicate that multicollinearity should not be a concern (Burns and Burns, 2008;
Hair et al., 2006; Pallant, 2010; Wang and Ahmed, 2009). Multicollinearity
manifests a statistical phenomenon in which two or more predictor variables in a
multiple regression model are highly correlated (usually α ≥0.80). It means that
one variable can be linearly predicted from the other(s) with a non-trivial degree of
accuracy. This would lead to the conclusion that some variables are measuring the
same thing and only one of them may be necessary. With low inter-correlations in
the present data set, estimates of coefficients of regression, correlation, and
determination are neither biased nor over-inflated.
Table 9.1a24- Correlations among all Variables
Results of the qualitative research in chapter 8 confirmed the proposed conceptual
model. Based on the variables in Table 9.1a, the subsequent sections report and
discuss the results after quantitatively testing for validity of the model (Figure 9.1).
Survey Research Findings
212
Figure 9.113- Quantitatively Tested Model for the Intervening Role of EE
Statistical Analyses - Rationale and Implication of Multiple Variables
The rationale for inclusion of variables at individual and institutional levels to
explore the influences on perceptions of feasibility and desirability of
entrepreneurship is discussed in Chapter 6 and the operationalisation of the
relevant constructs and assessment of their validity and reliability is covered in
chapter 7 sections 7.5 to 7.6. From the perspective of statistical analysis, when
multiple antecedents are involved, the rationale is that a combination of multiple
relevant independent variables would improve understanding of the influences on
the dependent variable i.e. perceptions of feasibility and desirability of
entrepreneurship (Caliendo, 2013). This is because multiple regression helps to
quantify the impact each independent variables has on the dependent variable
(based on regression coefficients, ‘b’, and their significance). In addition multiple
regression analysis also helps to show the degree to which the combined
influence of the independent variables account for the variation of the dependent
variable (based on multiple correlation coefficient, R, and coefficient of multiple
determination, R2).
Survey Research Findings
213
Omitted Variable Bias
One of the internal validity problems with regression analysis based on cross-
sectional data occurs when omitted variables affect the relationship between the
dependent variable and the included independent variables (Clarke, 2005;
Nikolova and Simroth, 2013). By definition an estimator (a statistic) is consistent
and unbiased if it converges in probability to the correct population value
(parameter) as the sample size grows (Wooldridge, 2012; Wooldridge, 2010). The
challenge of specifying a theoretical model is that it is practically impossible to
include every variable. This may be because the relevant variables do not exist in
the database being used (Bono and McNamara, 2011). Moreover, researchers
may be unaware that they are omitting an important variable (Leightner and Inoue,
2012). Therefore, careful attention to the inclusion of key variables during the
design stage can mitigate the problem of omitted variable bias (Bono and
McNamara, 2011). However, research can err on the side of too few or too many
variables. For this reason, some statisticians forthrightly argue that regression
equations based on a few variables are simply more accurate than regression
equations based on many variables (Breiman, 1992). In fact, prior empirical
research indicates that sometimes inclusion of irrelevant variables may produce
inefficient coefficient estimates. This may increase the bias (Clarke, 2005) .
Rationale for Control Variables for the Current Study
Prior empirical research in developed countries indicates that demographic
variables such as gender and age (BarNir et al., 2011; Henley, 2007; Verheul et
al., 2012) and non-demographic variables such as university type and degree type
(Levenburg et al., 2006; Luethje and Franke, 2004; Lüthje and Franke, 2003;
Martínez et al., 2010; Robinson and Sexton, 1994) have an influence on EI
because they are likely to affect perceptions that entrepreneurship is feasible and
Survey Research Findings
214
valuable. As a result, these variables were taken into account in the current study
as control variables when the effects of the hypothesised individual and
institutional factors on EI were assessed.
9.2 Regression Tests for the Entrepreneurial Intention Model
This section reports regression analyses results for tests of the basic EI model. EI
is critical to business start-up because it represents the state of mind that
precedes action (Shook et al., 2003; Thompson, 2009). In all the simple and
multiple regression analyses performed in the current study, low variance inflation
factors (VIF<5) further confirm that multicollinearity is not a concern (Burns and
Burns, 2008; Hair et al., 2006; Pallant, 2010; Wang and Ahmed, 2009). This
entails that estimates of coefficients of regression, correlation, and determination
are neither biased nor over-inflated. Table 9.1b reflects the actual signs indicating
direction of influence for regression coefficients. The discussion and interpretation
of regression results in the next subsections indicates that the influence of control
and independent variables on the dependent variables is in line with what has
been hypothesised.
Table 9.1b - Regression Coefficient Signs
# Variable EI Feasibility Desirability1 Entrepreneurial Intention
2 Feasibility +
3 Desirability +
4 Age + -
5 Gender + +
6 UniversityType-Private/ Public - +
7 DegreeType- Business or not + +
8 AchievementNeed + +
9 LocusOfControl + +
10 RiskTakingPropensity + +
11 PriorEntrepreneurialExposure + +
12 Normative + +
13 Regulatory + +
14 Cognitive + +
Survey Research Findings
215
Subsection 9.2.1 reports results of the effects of feasibility and desirability on EI.
Subsection 9.2.2 reports results of independent and control variables’ effects on
feasibility and desirability.
9.2.1 Effects of Perceived Feasibility and Desirability on EI
Table 9.2 reports the results of hierarchical multiple regression analyses
examining the unique and combined effects of perceived feasibility and desirability
of entrepreneurship on EI. Model 1 reports the effect of feasibility on EI. Model 2
reports the combined influence of feasibility and desirability on EI. All the
regression coefficients are in the expected direction (see Table 9.1b)
Table 9.225- Regression Analyses for Attitudinal Antecedents’ Influences on EI
As reflected in Table 9.2, the adjusted R squared (coefficient of determination) is
significantly different from zero in both models. Overall, 37.5 percent of the
variation of EI is explained by the combined effect of perceived feasibility and
desirability. Furthermore, both attitudinal antecedents uniquely and significantly
contribute to the prediction of EI (p<0.01). Specifically, perceived feasibility has a
significant effect on EI with a correlation coefficient of 0.477. The introduction of
desirability results in a sharp increase from 0.477 to a multiple correlation
coefficient of 0.615. This means that an individual with higher perceived feasibility
and desirability of entrepreneurship has higher EI. In other words, an increase in
Variables Model1 Model2
B(1), SE(1) B(2), SE(2)
Feasibility 0.463**, 0.041 0.214**, 0.045
Desirability 0.472**,0.047
F 125.094** 128.094**
F change 125.094** 102.653**
R 0.477 0.615
R sq 0.227 0.378
R sq adjusted 0.226 0.375
R sq change 0.227 0.151
df 1=1, 2, df2=? 431 429
Constant,SE 2.574**,0.155 1.466**,0.177
** signifcant at p<0.01 Note: All t values >2
Survey Research Findings
216
desirability and feasibility is associated with an increase in the level of intention to
start a business. Therefore, to increase EI, factors that influence perceived
feasibility and desirability of entrepreneurship should be considered. This result is
consistent with prior research that desirability and feasibility are the immediate
antecedents of EI (Fitzsimmons and Douglas, 2011; Krueger JR et al., 2000; Liñán
and Chen, 2009; Liñán et al., 2011a).
9.2.2 Determinants of Feasibility and Desirability
Extant literature indicates that there is little knowledge about the determinants of
perceived feasibility and desirability of entrepreneurship (Davidsson, 2004;
Schlaegel and Koenig, 2014). This subsection addresses this issue by examining
effects of individual and institutional factors on attitudinal antecedents of EI.
9.2.2.1 Effects of Institutional and Individual Factors on Perceived Feasibility
Table 9.3 reports the results of hierarchical multiple regression analyses executed
to determine the single and combined effects of control variables, individual and
institutional factors on perceived feasibility of entrepreneurship. All the regression
coefficients for independent and control variables are in the expected direction
(see Table 9.1b).
Table 9.326- Regression Analyses for Influences on Feasibility
Variables Model1 Model2 Model3
B(1), SE(1) B(2), SE(2) B(3), SE(3)
Control Variables
Age 0.014*, 0.007 0.011, 0.006 0.011, 0.006
gender 0.185**, 0.064 0.224**,0.060 0.210**,0.059
UniveristyType -0.022*, 0.090 -0.023, 0.086 -0.052,0.084
DegreeType 0.057, 0.090 0.037, 0.084 0.061,0.082
Individual Factors
Need for Achievement 0.149*,0.060 0.156**,0.058
Locus of Control 0.164**,0.043 0.143**,0.042
Risk taking 0.204**,0.038 0.219**,0.053
PriorEntExposure 0.300**,0.051 0.289**,0.049
Institutional Factors
Normative 0.115**,0.030
Regulatory 0.070*,0.033
Cognitive 0.118**,0.031
F 2.258* 22.969** 21.189**
F change 2.258* 39.728** 14.585**
R 0.147 0.428 0.487
R sq 0.025 0.183 0.238
R sq adjusted 0.020 0.175 0.226
R sq change 0.025 0.158 0.055
df 1=4, 8,11, df2=? 432 431 430
* significant at p<0.05; ** signifcant at p<0.01
Survey Research Findings
217
Firstly, Model 1 reports the base model only with control variables. The control
variables have a combined marginal but significant effect on feasibility with an
adjusted R2 of 2.0% and multiple correlation coefficient of 0.147. While degree
type does not have a significant effect, gender (p<0.01), age (p<0.05), and
university type (p<0.05) each has a significant effect. For degree type, the
rationale for a positive regression coefficient is that prior research indicates that an
understanding of business and its rewards increases perceptions that managing a
business is possible. Thus business degree students are expected to have higher
perception of feasibility (Martinez et al., 2010; BarNir et al., 2011).The result for
gender entails that males generally have higher perceived feasibility of
entrepreneurship than females. In relation to entrepreneurship, prior research
indicates that one explanation for low interest and self-efficacy is that women have
less early career experience or social support and fewer role models than their
male counterparts (BarNir et al., 2011; Dyer, 1994; Hisrich and Brush, 1985;
Scherer et al., 1990; Shinnar et al., 2012; Siu and Lo, 2013). Age has a significant
effect on perceived feasibility possibly because of two reasons i.e. employment
experience and self-employment experience. Based on Analysis of Variance
(ANOVA) tests (see Appendices 9.2, 9.3, 9.4 and 9.5), post-hoc checks indicate
that older respondents have significantly (p≤0.05) more employment and self-
employment experience than the younger respondents (Appendix 9.5). This
explanation is plausible because prior research, in the context of UK, indicates that
while desirability and EI may be higher among the younger and educated
individuals, the young may lack resources, skills and experience and hence their
perceived feasibility is likely to be lower (Henley, 2007).
Related to age, respondents from public universities have lower perceived
feasibility than those from private universities. This is possibly because of two
Survey Research Findings
218
related reasons. Firstly, compared to students at private universities (coded 0),
most students at public universities (coded 1) are generally younger. This is
because they enter tertiary education earlier i.e. a year after completing secondary
education. Secondly, because of the age difference, public university students
have less employment and self-employment experience (Appendices 9.1, 9.3, 9.4
and 9.5). This is corroborated further by chi-square tests indicating a significant
association between age and type of university, X2 (df=3,n=432)=12.368,p=0.004,
Cramer’s V=0.124. This result is expected in Zambia because students who
complete secondary education first compete for a place in public universities
where government bursaries are available. Unsuccessful applicants usually delay
entry into tertiary education due to challenges of school fees. Such school leavers,
assuming they are still interested in tertiary education, either wait for their
guardians or they themselves engage in viable activities to raise the required
funds. This delay entails that students at private universities, compared to those at
public universities, are generally older.
In relation to age and university type, the change from significant to insignificant
for the regression coefficients when individual factors and later institutional factors
are introduced may mean that the explanatory power of age and university type
diminishes when other variables at individual and institutional levels are
considered.
Secondly, when the individual factors are introduced in the regression (Model 2), a
significant additional overall effect on feasibility occurs (from 2% to 17.5% i.e. R2 Δ
=15.5%). Each individual factor, i.e. need for achievement (NAch), internal locus of
control (ILC), risk taking propensity (RTP) and prior entrepreneurial exposure
(PEE), has a significant (p<0.01) positive effect on feasibility. The combined
multiple correlation coefficient with feasibility has increased sharply in model 2
Survey Research Findings
219
(from R=0.147 to 0.428). This means that individuals with higher NAch, ILC, RTP
and PEE have higher perceived feasibility of entrepreneurship.
Thirdly, when institutional factors are introduced (Model 3), a significant additional
overall effect on feasibility occurs (from 17.5% to 22.6% i.e. R2 Δ=5.5%). The
significant multiple correlation coefficient increases from R=0.428 to R=0.487.
Among the institutional factors, normative (p<0.01), cognitive (p<0.01) and
regulatory (p<0.05) institutions have significant and positive effects on feasibility.
This means that favourable normative, cognitive, and regulatory institutions
increase perceived feasibility of entrepreneurship among potential entrepreneurs.
9.2.2.2 Effects of Individual and Institutional Factors on Perceived
Desirability
Table 9.4 reports results of hierarchical multiple regression analyses examining
the single and combined effects of control variables, individual and institutional
factors on perceived desirability of entrepreneurship. All the regression coefficients
for independent and control variables are in the expected direction (see Table
9.1b).
Table 9.427- Regression Analyses for Influences on Desirability
Survey Research Findings
220
Firstly, Model 1 reports the base model only with control variables. The control
variables have a combined marginal but significant effect on desirability with an
adjusted R2 of 1.6%. However, only gender has a significant effect (p<0.05). Age,
university type, and degree type do not have a significant unique effect. The
control variables’ overall combined effect is small but significant (R =0.161;
p≤0.05). In relation to gender, the results mean that males, compared to females,
have higher perceived desirability of entrepreneurship, a finding that is consistent
with prior research; the explanation is that males have more role models as well as
social support for entrepreneurship (Verheul et al., 2012).
For degree type, the rationale for a positive regression coefficient is that prior
research indicates that an understanding of business and its rewards increases
perceptions that managing a business is attractive. Thus business degree
students are expected to have higher perceptions of desirability (Martinez et al.,
2010; BarNir et al., 2011). Related to university type, respondents from public
universities are expected to have higher perceived desirability than those from
private universities). This is because, compared to students at private universities
(coded 0), most students at public universities (coded 1) are generally younger.
The reason is that they enter tertiary education earlier i.e. a year after completing
secondary education. This is corroborated further by chi-square tests indicating a
significant association between age and type of university, X2
(df=3,n=432)=12.368,p=0.004, Cramer’s V=0.124. This result is expected in
Zambia because students who complete secondary education first compete for a
place in public universities where government bursaries are available.
Unsuccessful applicants usually delay entry into tertiary education due to
challenges of school fees. Such school leavers, assuming they are still interested
in tertiary education, either wait for their guardians or they themselves engage in
Survey Research Findings
221
viable activities to raise the required funds. This delay entails that students at
private universities, compared to those at public universities, are generally older.
Prior research indicates that younger people often have higher desirability of
entrepreneurship. This is because entrepreneurship involves uncertainty which the
older individuals are reluctant to embrace (Henley, 2007).
In relation to age, the change from insignificant to significant for the regression
coefficients when individual factors and later institutional factors are introduced
indicates that the explanatory power of age increases when considered at the
same time as factors at individual and institutional levels. In this case, with an
increase in age, perceptions of desirability of entrepreneurship decrease for two
possible reasons. First, the older individuals, compared to the younger, are less
likely to be attracted to entrepreneurship because of the uncertainty concern
(Henley, 2007). Second, as indicated earlier, older individuals are not only more
likely to be in employment but they are also more likely to have family
commitments (CSO, 2013). This entails that older individuals face higher social
pressure not to engage in activities that are fraught with uncertainty such as
starting a business (Kennedy et al., 2003). This is especially relevant in a
collectivistic society such as Zambia.
Secondly, when the individual factors are introduced in the regression (Model 2), a
significant additional overall effect on desirability occurs (from 1.6% to 18.4% i.e.
R2 Δ = 16.8%). Each individual factor, that is, NAch (p<0.01), ILC (p<0.01), RTP
(p<0.01) and PEE (p<0.05), has a significant positive effect on desirability. The
combined effect for predictor variables has increased exponentially to 44.7% (R).
These results mean that high NAch, ILC, RTP and PEE lead to high perceived
desirability of entrepreneurship.
Survey Research Findings
222
Thirdly, when institutional factors are introduced in the regression (Model 3), a
significant additional overall effect on desirability occurs (from 18.4% to 20.3% i.e.
R2 Δ=1.9 %). Among the institutional factors, only normative institution has a
significant positive contribution (p<0.01); cognitive and regulatory institutions have
positive but insignificant effects on desirability. The combined effect for predictor
variables has increased from 44.7% to 47.3% (R).
9.2.2.3 Summary on Determinants of Feasibility and Desirability
Overall, based on the results of regression analyses, EI is parsimoniously a
function of perceived feasibility and desirability of entrepreneurship (Ajzen, 1991;
Shapero and Sokol, 1982). Individual and institutional factors influence EI via
perceived feasibility and desirability of entrepreneurship, an aspect of research
that has a shortage of empirical evidence in extant literature (Fayolle and Liñán,
2014; Schlaegel and Koenig, 2014; Rideout and Gray, 2013).
These findings are also in line with qualitative research results discussed in
chapter 8 section 8.1.1 and section 8.1.2. In section 8.1.1, the interviewees explain
that perceived support in the regulatory and normative institutions as well as
shared information in the cognitive institution help to reduce barriers, increase the
likelihood of support from stakeholders and therefore increase the perception that
business start-up is achievable. In addition, perceived support in the three
institutions signals to would-be entrepreneurs that entrepreneurship is important
and valuable for both individuals and the society. Therefore, favourable institutions
positively influence the intention to start a business. The findings show that
institutions have an impact at micro level because they influence EI through their
effects on perceived feasibility and desirability of entrepreneurship, an aspect of
research that is lacking in the extant literature (Fayolle and Liñán, 2014).
Survey Research Findings
223
In section 8.1.2, the interviewees explain that individuals are different in
personality, abilities, interests and background. Individuals with characteristics and
backgrounds aligned with the requirements of entrepreneurial tasks and activities
are more likely to find entrepreneurship attractive and viable. Therefore,
individuals with high NAch, RTP, ILC and PEE are more likely to start a business.
The results are consistent with prior research that PEE has a significant indirect
effect on EI through its influence on perceived feasibility and desirability (BarNir et
al., 2011; Carr and Sequeira, 2007; Guerrero et al., 2008; Krueger, 1993; Verheul
et al., 2012). However, in extant literature, there is a shortage of empirical
evidence in relation to the effect of RTP, ILC and NAch on EI via desirability and
feasibility (Frank et al., 2007; Lüthje and Franke, 2003; Segal et al., 2005).
9.3. Statistical Mediation Analyses
The empirical evidence in the preceding section supports the basic EI model that,
parsimoniously, individual and institutional factors influence EI through their effects
on perceived feasibility and desirability of entrepreneurship (Fitzsimmons and
Douglas, 2011; Ajzen 1991; Ajzen, 2011; Shapero and Sokol, 1982). This section
discusses contemporary procedures for examining the mediating role of EE on the
effects of individual and institutional factors on perceived feasibility and
desirability. The choice of mediation analysis is based on the general thesis
developed in the conceptual framework in Chapter 6 that individual and
institutional factors also influence effectiveness of EE. Mastery of entrepreneurship
knowledge and skills through EE then positively influences perceived feasibility
and desirability of entrepreneurship (see Figure 9.1 in section 9.1). Therefore, this
section explains the concept of mediation and outlines its procedures based on
contemporary guidelines in the literature.
Survey Research Findings
224
The Concept of Mediation The outcome of empirical research is more helpful to stakeholders’ understanding
of the research problem if it establishes not only whether X affects Y but also how
and when that relationship holds (Baron and Kenny, 1986; James and Brett, 1984;
Judd and Kenny, 1981a; Judd and Kenny, 1981b). Statistical mediation analysis
helps researchers to understand the different paths or mechanisms through which
an independent variable transmits its effect to a dependent variable (Hayes, 2013;
Jose, 2013; Judd and Kenny, 2010; Kenny, 2008; MacKinnon et al., 2012; Morera
and Castro, 2013; Rucker et al., 2011; Wood et al., 2008).
Figure 9.214- The Concept of Mediation
Clearly, from Figure 9.2, mediation analysis is important because it identifies the
process of transmission of an independent variable X’s effect on the dependent
variable Y. Specifically, the impact of X on Y may be exerted via two routes i.e. a
direct effect (path c’) and indirect effect (path ab) through a mediator variable (M).
Thus, mediation analysis provides a more detailed understanding of relationships
among variables (MacKinnon and Fairchild, 2009). To conduct mediation analysis,
a minimum sample size of 74 respondents is usually required (Fritz and
Mackinnon, 2007; Mackinnon et al., 2012; Shrout and Bolger, 2002).
Survey Research Findings
225
9.3.1 Statistical Mediation Analyses Procedures
There are several approaches to testing mediation (for comprehensive review see
Mackinnon et al., 2002 and Wood et al., 2008). However, the Baron and Kenny’s
(1986) causal steps approach is the most widely used. In this approach, several
regression analyses are undertaken and significance of the regression coefficients
is examined. Table 9.5 shows the contemporary steps for regression-based
mediation analyses.
Table 9.528- Statistical Mediation Analyses Procedures
Step Analysis Equation or Visual Depiction
Step 1
Simple regression analysis with M predicting Y to test the significance of path b Y=i1+bM+eY
(1)
Step 2
Simple regression analysis with X predicting Y for path c (total effect), Y=i2+cX+ey
(2)
Step 3
Simple regression analysis with X predicting M for path a, M=i3+aX+eM
( 3)
Step 4
Multiple regression analysis with X and M predicting Y to estimate path c’ (direct path) and b, Y=i4+c’X+bM+eY
(4)
Step 5
Test significance of the indirect effect , a X b=ab (i.e. ab=c-c’) by conducting Sobel's Z test or/and the contemporary more powerful tests for the indirect path (i.e. bootstrap or Monte Carlo confidence intervals)
(5)
Source: Kenny and Baron (1986); Zhao et al. (2010); Rucker et al., (2011); Hayes (2013); and, Jose (2013)
MacKinnon et al. (2002) categorised the regression-based tests of mediation into
three groups:
Causal steps approach requires that a, b, c (steps 2, 3, 4) be significant and
c’ insignificant for full mediation. Exceptions are made for significant c’ in
partial mediation (Kenny and Judd, 1981; James and Brett, 1984; Baron
and Kenny, 1986);
Survey Research Findings
226
Difference in coefficients tests i.e. c-c’ divided by the standard error of the
difference (Kenny and Judd, 1981). This value is then compared against a t
distribution to test for significance; and,
Product of coefficients tests (steps 3, 4, and 5) i.e. a X b divided by
standard error of the product (Sobel, 1982). This value is then compared
against a normal distribution to test for significance.
The causal steps approach has been the most widely used. In fact, 70.90% of
prior studies examining mediation have employed this approach (Fritz and
MacKinnon, 2007). However, based on recent empirical research, this approach is
inadequate for two major reasons. Firstly, it emphasises the need for significant
total effect (path c) and insignificant direct effect i.e. path c’ (MacKinnon et al.,
2012; Shrout and Bolger, 2002). Secondly, it does not really test the significance
of the compound pathway (path ab). Consequently, it is more prone to type II
errors i.e. it tends to miss some true mediation effects (MacKinnon et al., 2007).
Therefore, the preferable approaches calculate the indirect effect (path ab) and
test it for significance (Zhao et al., 2010). MacKinnon et al. (1995) shows that
difference in coefficients and product of coefficients yield identical values (c-c’ =
ab) as long as unstandardized coefficients are used for ordinary least squares
regression. Furthermore, a variation on the product-of-coefficients test uses
resampling. If many samples are taken from the original sample, with replacement,
the parameter of interest (indirect effect path ab) can be calculated for each new
sample. This forms a bootstrap distribution of that parameter, and confidence
intervals can be formed to test for mediation (Hayes, 2009; MacKinnon, 2007;
MacKinnon et al., 2002; Taylor et al., 2008; Wu and Zumbo, 2008; Zhao et al.,
2010b).
Survey Research Findings
227
9.4 The Mediating Role of Entrepreneurship Education
EI theories posit that individual and contextual factors influence EI through their
effects on perceived feasibility and desirability of entrepreneurship (Ajzen, 1991;
Ajzen, 2002; Ajzen, 2011b; Fitzsimmons and Douglas, 2011; Liñán et al., 2011a;
Shapero and Sokol, 1982). Based on empirical data from the current study, these
claims are supported as reported in section 9.2, subsections 9.2.1 and 9.2.2. This
section reports the results of analyses examining the mediating role of EE on the
effects of individual and institutional factors on perceived feasibility and
desirability.
9.4.1 EE Mediating the Effects of Institutions on Feasibility and Desirability
This subsection examines the mediating role of EE on the effects of institutional
factors on perceived feasibility and desirability of entrepreneurship. In the
mediational analyses, the dependent variables are feasibility and desirability. The
independent variables are institutional factors i.e. normative, cognitive and
regulatory institutions. The three mediator variables reflect perceptions of
effectiveness of EE i.e. perceived learning from the module, perceived practical
approaches (experiential learning) and perceived access/utilisation of relevant
resources during EE. Table 9.6 reports an example of detailed analyses executed.
Survey Research Findings
228
Table 9.629- EE Mediating the Influence of Normative Institution on Feasibility
In Table 9.6, perceived feasibility is the dependent variable (Y) and normative
institution is the independent variable (X). Accordingly, Model 1 and Model 2 have
perceived feasibility as the dependent variable. Firstly, Model 1 examines the
effect of normative institution on feasibility i.e. total effect (path c). Secondly,
Model 2 introduces the mediator variables (perceived learning for column 2,
practical approaches for column 3, access to resources for column 4). This
examines the mediator’s effect (path b) and the independent variable’s direct
effect (path c’) on the dependent variable. Thirdly, Model 3 shows the effect of the
independent variable on the mediators (perceived learning for column 2, practical
approaches for column 3, access to resources for column 4). This examines the
effect of the independent variable, i.e. normative institution, on the mediator (path
a). Fourthly, the bottom row in Table 9.6 reports the results of Sobel’s Z test for
significance of the indirect effect (path ab). Where the Sobel test result is not
significant, the more powerful (bootstrapping) 95% confidence interval results are
considered to reduce type II error (Naylor et al., 2012; Zhao et al., 2010;
Mackinnon et al., 2007). Lastly, where the direct effect (path c’) is significant, the
Models 1 & 2 Mediator: Perceived Learning Mediator: Practical Approaches Mediator:Access to Resources
Dependent
Variable=
Feasibility Model assessments (1) Model assessments (2) Model assessments (3)
Variables B(1) t (1) Sig. (1) F (sig), R, R sq, Rsq adj. B(2) t (2) Sig.(2) F (sig), R, R sq, R sq adj. B(3) t (3) Sig. (3) F (sig), R, R sq, R sq adj.
1 (Constant) 2.694 16.964 0.000 F=26.933 (p=0.000) 2.694 16.907 0.000 F=26.752(p=0.000) 2.694 16.907 0.000 F=26.752(p=0.000)
Normative(c) 0.217 5.190 0.000 R=0.238, Rsq=0.057 0.217 5.172 0.000 R=0.238, Rsq=0.057 0.217 5.172 0.000 R=0.238, Rsq=0.057
Rsq adj=0.055 Rsq adj=0.055 Rsq adj=0.055
2 (Constant) 1.411 6.217 0.000 F=43.404 (p=0.000) 2.337 13.795 0.000 F=27.738(p=0.000) 2.237 12.037 0.000 F=24.224(p=0.000)
Normative(c') 0.132 3.219 0.001 FΔ (56.529, p=0.000) 0.150 3.510 0.000 FΔ (27.148, p=0.000) 0.156 3.605 0.000 FΔ (20.520, p=0.000)
Mediator (b) 0.380 7.519 0.000 R=0.404, Rsq=0.163 0.197 5.210 0.000 R=0.334, Rsq=0.111 0.212 4.530 0.000 R=0.314, Rsq=0.099
Rsq adj=0.159 Rsq adj=0.107 Rsq adj=0.095
3 (Constant) 3.372 24.109 0.000 F=36.787 (p=0.000) 1.815 9.349 0.000 F=44.221(p=0.000) 2.162 13.647 0.000 F=48.044(p=0.000)
Normative(a) 0.223 6.065 0.000 R=0.275, Rsq=0.076 0.340 6.650 0.000 R=0.301, Rsq=0.090 0.289 6.931 0.000 R=0.312, Rsq=0.098
Rsq adj=0.074 Rsq adj=0.088 Rsq adj=0.096
Sobel test (ab) B1 Z Sig. B2 Z Sig. B3 Z Sig.
Mediation 0.086 4.146 0.000 0.068 3.696 0.000 0.063 3.349 0.001
Type (abc') 0.01 complementary 0.010 complementary 0.010 complementary
M
o
d
e
l
Survey Research Findings
229
sign for the product of the three coefficients abc’ determines the type of mediation
(Baron and Kenny, 1986; Zhao et al. 2010).
Consistent with the steps illustrated in Table 9.6, the results for perceptions of
effectiveness of EE as possible mediators for each institutional factor’s effects on
feasibility and desirability are reported in the Appendices. Appendix 9.6 for
normative institution, Appendices 9.7 and 9.8 for cognitive institution as well as
Appendices 9.9 and 9.10 for regulatory institution. Table 9.7 reports the summary
of regression coefficients and their tests of significance in line with hypothesised
mediational relationships for each institutional factor.
Table 9.730- Summary of Results for EE Mediating Institutional Factors’ Effects on Attitudes
9.4.1.1 Normative Institution’s Effects on Feasibility and Desirability Mediated by
EE
Firstly, Table 9.7 reports that the indirect effect (path ab) of the normative
institution on perceived feasibility, through its influence on perceptions of
effectiveness of EE, is positive and significant. This is supported by all three
1 Normative Learning Feasibility 0.217** 0.132** 0.380** 0.223** 0.086** Complementary
2 Normative Practical Approaches Feasibility 0.217** 0.150** 0.197** 0.340** 0.068** Complementary
3 Normative Access to Resources Feasibility 0.217** 0.156** 0.212** 0.289** 0.063** Complementary
4 Normative Learning Desirability 0.186** 0.108** 0.350** 0.223** 0.075** Complementary
5 Normative Practical Approaches Desirability 0.186** 0.137** 0.145** 0.340** 0.047** Complementary
6 Normative Access to Resources Desirability 0.186** 0.163** 0.080 0.289** 0.022 Direct only Non-mediation
7 Cognitive Learning Feasibility 0.173** 0.134** 0.406** 0.097* 0.041* Complementary
8 Cognitive Practical Approaches Feasibility 0.173** 0.121** 0.214** 0.245** 0.054** Complementary
9 Cognitive Access to Resources Feasibility 0.173** 0.141** 0.242** 0.134** 0.034* Complementary
10 Cognitive Learning Desirability 0.009 -0.029 0.391** 0.097* 0.039* Indirect only mediation
11 Cognitive Practical Approaches Desirability 0.009 -0.037 0.188** 0.245** 0.047** Indirect only mediation
12 Cognitive Access to Resources Desirability 0.009 -0.010 0.137** 0.134** 0.019* Indirect only mediation
13 Regulatory Learning Feasibility 0.117* 0.080 0.417** 0.089* 0.037* Indirect only mediation
14 Regulatory Practical Approaches Feasibility 0.117* 0.071 0.228** 0.202** 0.046** Indirect only mediation
15 Regulatory Access to Resources Feasibility 0.117* 0.079 0.253** 0.152** 0.038** Indirect only mediation
16 Regulatory Learning Desirability 0.011 -0.024 0.389** 0.089* 0.033* Indirect only mediation
17 Regulatory Practical Approaches Desirability 0.011 -0.027 0.185** 0.202** 0.035** Indirect only mediation
18 Regulatory Access to Resources Desirability 0.011 -0.010 0.137** 0.152** 0.021* Indirect only mediation
Note: ** significant at 0.01 level * significant at 0.05 level
Effect of
IV on
Mediator
(a)
Indirect
effect
(ab)
Type of Mediation
Unique
Effect of
Mediator
(b)
M
o
d
e
l
Independent
VariableMediating Variable
Dependent
Variable
Total
effect
( c)
Direct
effect
(c' )
Survey Research Findings
230
mediational statistics for the product of coefficients (ab): perceived learning
(ab=0.086**, Z=4.146, p=0.000), perceived practical approaches (ab=0.068**,
Z=3.696, p=0.000), and perceived access to resources (ab=0.063**, Z=3.349,
p=0.001). This is a consequence of the normative institution’s effect on perceived
learning, perceived practical approaches and perceived access to resources,
which in turn influence perceived feasibility. Since the direct effect paths (c’) are
significant (p<0.01), the type of mediation is complementary i.e. both the indirect
paths and direct paths are significantly positive.
Furthermore, Table 9.7 reports that the indirect effect (ab) of the normative
institution on perceived desirability, through its influence on perceptions of
effectiveness of EE, is positive but only significant for perceived learning and
practical approaches. This is corroborated by the mediational statistics for the
product of coefficients (ab): perceived learning (ab=0.075**, Z=3.761, p=0.000),
practical approaches (ab=0.047**, Z=3.067, p=0.002), and access to resources
(ab=0.022, Z=1.541, p=0.123). This is a result of the normative institution’s effect
on perceived learning, practical approaches and access to resources, which in
turn influence desirability. Since all the direct effect paths (c’) are significant
(p<0.01), the type of mediation is complementary for perceived learning and
practical approaches i.e. both the mediational paths and direct paths are positive
and significant. However, for access to resources, while the mediational path is
insignificant, the direct path is positive and significant, which means the mediation
effect does not exist in this case.
9.4.1.2 Cognitive Institution’s Effects on Feasibility and Desirability Mediated
by EE
Secondly, Table 9.7 reports that the indirect effect (path ab) of the cognitive
institution on feasibility, through its effect on perceptions of effectiveness of EE, is
Survey Research Findings
231
positive and significant. This is substantiated by all three mediational statistics for
the product of coefficients (ab): perceived learning (ab=0.041*, Z=2.429, p=0.015),
practical approaches (ab=0.054**, Z=3.311, p=0.001), and access to resources
(ab=0.034*, Z=2.431, p=0.015). This is a consequence of the cognitive institution’s
effect on perceived learning, practical approaches and access to resources, which
then influence perceived feasibility. Since the direct effect paths (c’) are significant
(p<0.01), the type of mediation is complementary i.e. both the mediational paths
and direct paths are positive and significant.
Furthermore, Table 9.7 reports that the indirect effect (path ab) of the cognitive
institution on desirability of entrepreneurship, through its effect on perceptions of
effectiveness of EE, is positive and significant. This is validated by the mediational
statistics for the product of coefficients (ab): perceived learning (ab=0.039*,
Z=2.373, p=0.018), practical approaches (ab=0.047**, Z=3.273, p=0.001), and
access to resources (ab=0.019*, Z=2.020, p=0.043). This is a consequence of the
cognitive institution’s effect on perceived learning, practical approaches and
access to resources, which in turn influence desirability. Since all the direct effect
paths (c’) are insignificant (for all three, p> 0.05), the type of mediation is indirect
only i.e. while the mediational paths are positive and significant, direct effect paths
are insignificant.
9.4.1.3 Regulatory Institution’s Effects on Feasibility and Desirability
Mediated by EE
Thirdly, Table 9.7 reports that the indirect effect (ab) of the regulatory institution
on feasibility, through its effect on perceptions of effectiveness of EE, is positive
and significant. This is validated by all three mediational statistics for the product
of coefficients (ab): perceived learning (ab=0.037**, Z=2.015, p=0.044), practical
approaches (ab=0.046**, Z=2.951, p=0.003), and access to resources
Survey Research Findings
232
(ab=0.038**, Z=2.668, p=0.008). This is a consequence of the regulatory
institution’s effect on perceived learning, practical approaches and access to
resources, which in turn influence perceived feasibility. Since the direct effect
paths (c’) are all insignificant (for all three, p>0.05), the type of mediation is indirect
only i.e. while the mediational paths are significant, the direct paths are
insignificant.
Furthermore, Table 9.7 reports that the indirect effect (ab) of the regulatory
institution on desirability of entrepreneurship, through its influence on perceptions
of effectiveness of EE, is positive and significant. This is corroborated by the
significant mediational statistics for the product of coefficients (ab): perceived
learning (ab=0.033*, Z=2.017, p=0.044), practical approaches (ab=0.035**,
Z=2.791, p=0.005), and access to resources (ab=0.021*, Z=2.215, p=0.027). This
is a result of the regulatory institution’s effect on perceived learning, practical
approaches and access to resources, which in turn influence desirability. Since all
the direct effect paths (c’) are insignificant (for all three, p>0.05), the type of
mediation is indirect only i.e. while the mediational paths are positive and
significant, direct paths are insignificant.
9.4.1.4 Summary of Mediating Role of EE on Institutions’ Influences
The overall meaning of the preceding findings is that if potential entrepreneurs
perceive that institutional factors are favourable, this positively influences
perception of effectiveness of EE. Perception of mastery of entrepreneurship
knowledge and skills through EE in turn influences perceived feasibility and
desirability of new venture creation. Therefore, effectiveness of EE should be
examined in the context of the entrepreneurial environment of the potential
entrepreneurs. These findings are also consistent with qualitative research results
discussed in section 8.2.1. The interviewees explain that favourable normative,
Survey Research Findings
233
regulatory and cognitive institutions drive people to EE in two ways. Firstly, they
promote the status of entrepreneurship in societies and secondly, through lowering
of barriers, they influence people’s mindset that business start-up is viable.
Consequently, favourable institutions also affect the level of interest in EE. This
influences attitudes and effort as well as the consequent performance in EE.
Performance in EE is reflected in the level of entrepreneurship knowledge and
skills acquired. Through clarifying the benefits of entrepreneurship and developing
the required capabilities, EE then influences perception that business start-up is
not only worthwhile but also possible. .
The findings show that institutions have an impact at micro level because they
exert their influence on EI not only through perceived feasibility and desirability of
entrepreneurship but also through their effects on EE, an aspect of research that is
lacking in the extant literature (Bruton et al., 2010; De Clercq et al., 2011; Wicks,
2001). The GEM special report on entrepreneurship training (Martinez et al., 2010)
observes that training doubles EI in developing countries (2.2 times) compared to
developed countries (1.9 times). However, the gain in total early entrepreneurial
activity (TEA) due to entrepreneurship training is higher in developed countries
(2.1 times) than developing countries (1.5 times). The authors, without empirical
evidence and testing, attribute the difference to more favourable entrepreneurship
support mechanisms in developed countries than developing countries (see
Appendices 9.19 and 9.20). The research findings generated from the current
study can, to a certain extent, corroborate this perspective.
9.4.2 EE Mediating the Effects of Individual Factors on Feasibility and
Desirability
This subsection examines the mediating role of EE on the effects of individual
factors on perceived feasibility and desirability of entrepreneurship. In the
Survey Research Findings
234
mediational analyses, the dependent variables are feasibility and desirability. The
independent variables are individual factors: risk taking propensity (RTP), internal
locus of control (ILC), need for achievement (NAch), and prior entrepreneurial
exposure (PEE). The three mediator variables are perceptions of effectiveness of
EE: perceived learning from the module, perceived practical approaches
(experiential learning) and perceived access/utilisation of relevant resources.
Consistent with the steps shown in Table 9.6, the detailed results for perceptions
of effectiveness of EE as mediators for each individual factor are provided in the
appendices. Appendices 9.11 and 9.12 for RTP, Appendices 9.13 and 9.14 for
ILC, Appendices 9.15 and 9.16 for NAch, as well as Appendices 9.17 and 9.18 for
PEE. Table 9.8 reports the summary of regression coefficients and their tests of
significance in line with hypothesised mediational relationships for individual
factors.
Table 9.831- Summary of Results for EE Mediating Individual Factors’ Effects on Attitudes
1 RiskTakingPro Learning Feasibility 0.321** 0.237** 0.369** 0.226** 0.078** Complementary
2 RiskTakingPro Practical Approaches Feasibility 0.321** 0.273** 0.202** 0.235** 0.046** Complementary
3 RiskTakingPro Access to Resources Feasibility 0.321** 0.267** 0.210** 0.255** 0.053** Complementary
4 RiskTakingPro Learning Desirability 0.332** 0.259** 0.325** 0.226** 0.068** Complementary
5 RiskTakingPro Practical Approaches Desirability 0.332** 0.298** 0.144** 0.235** 0.034** Complementary
6 RiskTakingPro Access to Resources Desirability 0.332** 0.314** 0.071 0.255** 0.018 Direct only Non-mediation
7 LocusOfControl Learning Feasibility 0.301** 0.156** 0.369** 0.393** 0.141** Complementary
8 LocusOfControl Practical Approaches Feasibility 0.301** 0.255** 0.210** 0.221** 0.044** Complementary
9 LocusOfControl Access to Resources Feasibility 0.301** 0.252** 0.225** 0.220** 0.051** Complementary
10 LocusOfControl Learning Desirability 0.303** 0.176** 0.323** 0.393** 0.120** Complementary
11 LocusOfControl Practical Approaches Desirability 0.303** 0.269** 0.153** 0.221** 0.032* Complementary
12 LocusOfControl Access to Resources Desirability 0.303** 0.283** 0.092* 0.220** 0.021* Complementary
13 AchievementNeed Learning Feasibility 0.246** 0.106* 0.385** 0.361** 0.123** Complementary
14 AchievementNeed Practical Approaches Feasibility 0.246** 0.198** 0.213** 0.223** 0.045** Complementary
15 AchievementNeed Access to Resources Feasibility 0.246** 0.196** 0.231** 0.214** 0.049** Complementary
16 AchievementNeed Learning Desirability 0.306** 0.192** 0.314** 0.361** 0.103** Complementary
17 AchievementNeed Practical Approaches Desirability 0.306** 0.272** 0.149** 0.223** 0.032** Complementary
18 AchievementNeed Access to Resources Desirability 0.306** 0.287** 0.086* 0.214** 0.017* Complementary
19 PriorEntExpo Learning Feasibility 0.404** 0.329** 0.391** 0.191** 0.073** Complementary
20 PriorEntExpo Practical Approaches Feasibility 0.404** 0.367** 0.219** 0.171* 0.036* Complementary
21 PriorEntExpo Access to Resources Feasibility 0.404** 0.369** 0.242** 0.145* 0.034* Complementary
22 PriorEntExpo Learning Desirability 0.193** 0.122 0.374** 0.191** 0.068** Indirect only mediation
23 PriorEntExpo Practical Approaches Desirability 0.193** 0.164* 0.173** 0.171* 0.028* Complementary
24 PriorEntExpo Access to Resources Desirability 0.193** 0.175** 0.125** 0.145* 0.018* Complementary
Note: ** significant at 0.01 level * significant at 0.05 level
Effect of
IV on
Mediator
(a)
Indirect
effect
(ab)
Type of Mediation
Unique
Effect of
Mediator
(b)
M
o
d
e
l
Independent
VariableMediating Variable
Dependent
Variable
Total
effect
( c)
Direct
effect
(c' )
Survey Research Findings
235
9.4.2.1 Risk Taking Propensity’s Effects on Feasibility and Desirability
Mediated by EE
Firstly, Table 9.8 reports that the indirect effect (ab) of risk taking propensity
(RTP) on perceived feasibility, through its influence on perceptions of
effectiveness of EE, is positive and significant. This is verified by all three
mediation statistics for the product of coefficients (ab): perceived learning (ab=
0.078**, Z=3.471, p=0.001), practical approaches (ab=0.046**, Z=2.934, p=0.003),
and access to resources (ab=0.053**, Z=3.163, p=0.002). This is a consequence
of RTP’s effect on perceived learning, practical approaches and access to
resources, which in turn influence perceived feasibility. Since the direct effect
paths (c’) are all significant (p<0.01), the type of mediation is complementary i.e.
both the mediational paths and direct paths are significantly positive.
Furthermore, Table 9.8 reports that the indirect effect (ab) of RTP on perceived
desirability, through its influence on perceptions of effectiveness of EE, is positive
but only significant for perceived learning and practical approaches. This is
confirmed by the mediation statistics for the product of coefficients (ab): perceived
learning (ab=0.068**, Z=3.268, p=0.001), practical approaches (ab=0.034*,
Z=2.692, p=0.007), and access to resources (ab=0.018, Z=1.561, p=0.118). This
is a consequence of RTP’s effect on perceived learning, practical approaches and
access to resources, which in turn influence desirability. Since all the direct effect
paths (c’) are significant (p<0.01), the type of mediation is complementary for
perceived learning and practical approaches i.e. both the mediational paths and
direct paths are positive and significant. However, for access to resources, the
mediational path is insignificant while the direct path is significantly positive.
Survey Research Findings
236
9.4.2.2 Locus of Control’s Effects on Feasibility and Desirability Mediated by
EE
Secondly, Table 9.8 reports that the indirect effect (ab) of internal locus of control
(ILC) on feasibility, through its influence on perceptions of effectiveness of EE, is
positive and significant. This is confirmed by mediation statistics for the product of
coefficients (ab): perceived learning (ab=0.141**, Z=4.135, p=0.000), practical
approaches (ab=0.044**, Z=2.577, p=0.010), and access to resources
(ab=0.051**, Z=2.871, p=0.004). This is a result of ILC’s effect on perceived
learning, practical approaches and access to resources, which sequentially
influence perceived feasibility. Since the direct effect paths (c’) are all significant
(p<0.01), the type of mediation is complementary i.e. both the mediational paths
and direct paths are significantly positive.
Furthermore, Table 9.8 reports that the indirect effect (ab) of ILC on desirability,
through its influence on the perceptions of effectiveness of EE, is positive and
significant. This is verified by mediation statistics for product of coefficients (ab):
perceived learning (ab=0.120**, Z=3.846, p=0.000), practical approaches
(ab=0.032*, p=2.475, p=0.013), and access to resources (ab=0.021*, Z=1.985,
p=0.049). This is a consequence of ILC’s effect on perceived learning, practical
approaches and access to resources, which in turn influence desirability. Since all
the direct effect paths (c’) are significant (p<0.01), the type of mediation is
complementary i.e. both the mediational paths and direct paths are significantly
positive.
9.4.2.3 Need for Achievement’s Effects on Feasibility and Desirability
Mediated by EE
Thirdly, Table 9.8 reports that the indirect effect (ab) of need for achievement
(NAch) on feasibility, through its influence on perceptions of effectiveness of EE, is
positive and significant. This is verified by the mediation statistics for the product of
Survey Research Findings
237
coefficients (ab): perceived learning (ab=0.123**, Z=3.980, p=0.000), practical
approaches (ab=0.045*, Z=2.783, p=0.005), and access to resources (ab=0.049**,
Z=2.929, p=0.003). This is a consequence of the NAch’s effect on perceived
learning, practical approaches and access to resources, which sequentially
influence perceived feasibility. Since the direct effect paths (c’) are significant for
practical approaches (p<0.01), access to resources (p<0.01) and perceived
learning (p<0.05), the type of mediation is complementary i.e. both the mediation
paths and direct paths are significantly positive.
Furthermore, Table 9.8 reports that the indirect effect (ab) of NAch on perceived
desirability, through its influence on perceptions of effectiveness of EE, is positive
and significant. This is supported by the mediation statistics for the product of
coefficients (ab): perceived learning (ab=0.103**, Z=3.748, p=0.000), practical
approaches (ab=0.032*, Z=2.634, p=0.008), and access to resources (ab=0.017*,
Z=1.996, p=0.047). This is a consequence of the NAch’s effect on perceived
learning, practical approaches and access to resources, which in turn influence
perceived desirability. Since all the direct effect paths (c’) are significant (p<0.01),
the type of mediation is complementary i.e. both the mediation paths and direct
paths are significantly positive.
9.4.2.4 Prior Entrepreneurial Exposure’s Effects on Feasibility and
Desirability Mediated by EE
Fourthly, Table 9.8 reports that the indirect effect (ab) of prior entrepreneurial
exposure (PEE) on perceived feasibility, through its influence on perceptions of
effectiveness of EE, is positive and significant. This is verified by the mediation
statistics for the product of coefficients (ab): perceived learning (ab=0.073**,
Z=2.877, p=0.004), practical approaches (ab=0.036*, Z=1.998, p=0.049), and
access to resources (ab=0.034*, Z=1.988, p=0.047). This is a result of PEE’s
Survey Research Findings
238
effect on perceived learning, practical approaches and access to resources, which
sequentially influence perceived feasibility. Since all the direct effect paths (c’) are
significant (p<0.01), the type of mediation is complementary i.e. both the mediation
paths and direct paths are significantly positive.
Lastly, Table 9.8 reports that the indirect effect (ab) of PEE on perceived
desirability, through its influence on perceptions of effectiveness of EE, is positive
and significant. This is substantiated by mediation statistics for the product of
coefficients (ab): perceived learning (ab=0.068**, Z=2.814, p=0.005), practical
approaches (ab=0.028*, Z=1.998, p=0.048), and access to resources (ab=0.018*,
Z=1.992, p=0.046). This is a consequence of PEE’s effect on perceived learning,
practical approaches and access to resources, which in turn influence perceived
desirability. Since the direct effect paths (c’) are significant for practical
approaches (p<0.01) and access to resources (p<0.05), the type of mediation is
complementary i.e. both the mediation paths and direct paths are significantly
positive. However, for perceived learning, the type of mediation is indirect-only i.e.
the indirect path is significant while the direct path is insignificant.
9.4.2.5 Summary of Mediating Role of EE on Individual Factors’ Influences
The overall meaning of the preceding results is that EE participants have different
individual characteristics and backgrounds. This is because individuals differ in
ability, temperament, personality, interests, and upbringing/socialisation. Some
characteristics on which individuals differ determine whether one finds the tasks,
roles, and activities of entrepreneurship attractive and viable. Thus, individuals
with relevant individual factors enter the EE course/module with more favourable
attitudes (predispositions) to the notion of business start-up. This favourable
predisposition affects EE in terms of effort, zeal, and receptiveness. Consequently,
it affects perceived and actual mastery of entrepreneurship knowledge and skills
Survey Research Findings
239
acquired through EE. This in turn leads to higher perceived feasibility and
desirability of entrepreneurship.
These findings also echo qualitative findings discussed in section 8.2.2. The
interviewees explain that individuals with characteristics and backgrounds aligned
to entrepreneurship, such as high NAch, RTP, ILC and PEE, have higher odds of
starting a business and achieving higher learning outcomes in EE. This is because
such individuals already find entrepreneurship attractive and so they are likely to
apply themselves more during the training; such individuals are more eager to
learn about how to be successful at what they already like. This would reflect in
differences in the level of knowledge and skills acquired through EE. Since EE
develops entrepreneurial capabilities and clarifies the benefits of entrepreneurship,
such individuals would find entrepreneurship even more attractive and achievable
after the EE.
The possibility that individual factors’ effects on perceived feasibility and
desirability of entreprenurship are mediated by perceptions of effectiveness of EE
has not been empirically examined in prior research. This finding is consistent with
observations in extant literature that attitude and interest toward a subject
influence effort in learning and the consequent performance (Blickle, 1996;
Chamorro‐Premuzic and Furnham, 2003; De Fruyt and Mervielde, 1996; Lewis et
al., 2009; Lievens et al., 2002; Matlay, 2010). Specifically in relation to a career in
entrepreneurship, one study in the context of the USA finds that individuals with
higher RTP seem to benefit more from entrepreneurship training. This is because
they have higher business creation and ownership rates after the training (Fairlie
and Holleran, 2011). That study was based on longitudinal survey results from the
Department of Labour for Growing America Through Enterprise (GATE) project
that enrolled adults for free training and coaching in business creation and
Survey Research Findings
240
management. Peterman and Kennedy (2003) in Australia find that individuals with
prior entrepreneurial exposure are more likely to choose to participate in EE. This
may mean that individuals with prior exposure are more interested in
entrepreneurship and so they would like to learn more about how to become
successful entrepeneurs. Scholars indicate the need to explore if, why and how
EE and its impact differ in different learning contexts and with different individuals
(Rideout and Gray, 2013; Wang and Hugh, 2014). However, hitherto, no empricial
study has developed, tested and validated a conceptual model to reflect these
suggestions.
9.5 Conclusions
This chapter has reported the correlation, regression and mediation analyses
results of the quantitative research. The results are discussed and interpreted
based on findings from qualitative research and prior research. Firstly, the findings
show that entrepreneurial intention (EI) is parsimoniously a function of perceived
feasibility and desirability of entrepreneurship; the two attitudinal antecedents are
the major predictors of EI. Secondly, the results have shown that individual and
institutional factors are positively associated with perceived feasibility and
desirability. Individual factors include risk-taking propensity, internal locus of
control, need for achievement and prior entrepreneurial exposure. Institutional
factors include normative, cognitive, and regulatory institutions. Perceived
feasibility and desirability of entrepreneurship then influence EI. Until the current
study, the influence of normative, cognitive and normative institutions on perceived
feasibility and desirability of entrepreneurship has not been empirically
investigated.
Survey Research Findings
241
Thirdly, the findings show that effectiveness of EE mediates the effects of
individual and institutional factors on perceived feasibility and desirability of
entrepreneurship. Perceived learning from the module, access to resources and
practical approaches (experiential learning) reflect effectiveness of EE. The
mediational role of EE entails that individual and institutional factors transmit their
effects on perceived feasibility and desirability in two ways: a) direct influence on
perceived feasibility and desirability; and b) indirect influence on perceived
desirability and feasibility via effectiveness of EE. Until the current study, the
possibility that EE may have a mediatory role has not been empirically examined.
Lastly, scholars indicate the need to explore if, why and how EE and its impact
differ in different learning contexts and with different individuals (Rideout and Gray,
2013; Wang and Hugh, 2014). Moreover, De Clercq et al. (2011) recommend that
future studies should investigate combinations of individual and institutional
factors’ effects on perceived feasibility to start a business. However, hitherto, no
empricial study has developed, tested and validated a conceptual model to reflect
these suggestions. Clearly, the results have shown that individual factors and
institutional factors are primary while EE provides additional avenue/mechanism
for individual and institutional factors to influence EI.
The next chapter summarises the major findings of the study, highlights the
contributions to knowledge, and discusses implications of the findings to policy
and practice. The chapter also discusses the limitations of the study and identifies
areas for further research.
242
CHAPTER 10: CONCLUSIONS AND RECOMMENDATIONS
10.0 Introduction
Based on the literature review, this study aims to explore and examine individual
and institutional determinants of entrepreneurial intention (EI). Additionally, it
seeks to explore the effect of entrepreneurship education (EE) on the relationships
between EI and its determinants. Specifically, the current research’s objectives
are:
To examine the influence of institutional factors on entrepreneurial intention;
To investigate the influence of individual factors on entrepreneurial
intention; and,
To explore and examine if entrepreneurship education has an intervening
role on the effects of institutional and individual factors on entrepreneurial
intention.
The preceding two chapters, 8 and 9, discuss the results of the current research.
This chapter aims to highlight the major findings (section 10.1), contributions to
knowledge (section 10.2) as well as implications for policy and practice (section
10.3). The chapter also outlines limitations of the current study and recommends
directions for future research (section 10.4).
10.1 Findings and Conclusions of the Research
A detailed literature review exploring research on the effect of EE on EI shows
mixed conclusions (Bae et al., 2014; Fayolle and Liñán, 2014; Küttim et al., 2014);
while some studies find positive impact (Farashah, 2013; Fayolle et al., 2006a;
Fayolle and Gailly, 2009; Peterman and Kennedy, 2003; Solesvik et al., 2013;
Research Conclusions
243
Souitaris et al., 2007; Zhang et al., 2013), others report a negative impact or no
influence at all (Aouni and Pirnay, 2009; do Paço et al., 2013; Guerrero et al.,
2008; Marques et al., 2012; Oosterbeek et al., 2010; Tegtmeir, 2012; von
Graevenitz et al., 2010; Walter et al., 2011). In addition, there is a shortage of
studies examining the effect of institutional factors on EI (Schlaegel and Koenig,
2014; Wicks, 2001; Bruton et al., 2010; Fayolle and Liñán, 2014). In particular,
researchers recognise the lack of integrative models in examining the combined
influence of EE, individual and contextual factors on EI (Cope, 2005; De Clercq et
al., 2011; Fayolle and Liñán, 2014; Rideout and Gray, 2013; Wang and Chugh,
2014). Further, most studies on determinants of EI and entrepreneurial activity
employ quantitative strategies and are conducted in developed countries, limiting
the generalisability of their findings elsewhere (Bruton et al., 2010; Gartner, 2010;
Hoskisson et al., 2011; Iakovleva et al., 2011; Nabi and Liñán, 2011; Solesvik et
al., 2013; Solesvik et al., 2013; Solomon, 2007). Combinations of positivistic
research (addressing ‘what’ issues) and interpretivistic research (addressing the
‘why’ and ‘how’ issues) are rare and yet important for model testing and in-depth
understanding of phenomena (De Clercq et al., 2011; Fayolle and Liñán, 2014;
Gartner, 2010; Shook et al., 2003; Stevenson and Jarillo, 1990; van Burg and
Romme, 2014; Wang and Chugh, 2014).
In light of the foregoing considerations, the overall aim of the current research was
to investigate if EE has an intervening role on the effects of individual and
institutional factors on EI. Based on a review of the literature, a conceptual model
was developed and reflected in Chapter 6. In the proposed model, the variables
comprised the following:
individual variables: risk taking propensity, internal locus of control, need for
achievement and prior entrepreneurial exposure;
Research Conclusions
244
institutional variables: normative, cognitive and regulatory institutions;
intervening variables: effectiveness of EE, indicated by perceived learning
from the module, perceived access to resources and perceived practical
approaches (experiential learning) during EE; and,
dependent variables: EI and its attitudinal antecedents i.e. perceived
feasibility and desirability of entrepreneurship.
To avoid bias from utilising one particular methodology, this study employed a
concurrent triangulation strategy. This was intended for model testing and in-depth
understanding of the research issues in the Zambian context. Primary data were
collected from Zambia via qualitative interviews and a quantitative survey. For the
qualitative study, the interviewees included final year undergraduate students,
educators and practitioners in enterprise support organisations. The interview data
were analysed using Nvivo software. The findings from the interviews are
discussed in chapter 8. For the quantitative study, the survey was based on a
sample drawn from final year undergraduate students in Zambia. The survey data
were analysed using SPSS. The findings from the survey are discussed in chapter
9. Questionnaire items/constructs were adopted/adapted from prior studies. The
exception to this was one of the measures of effectiveness of EE i.e. perceived
experiential learning (practical approaches), which was developed based on the
literature review.
The survey data were subjected to factor and reliability analyses for the constructs
development. The results of factor and reliability analyses are reported and
discussed in chapter 7. Most of the Cronbach alphas for constructs were either at
0.70 or higher. Only one construct had an alpha value below 0.70. This was risking
taking propensity with an alpha value of 0.62, which was still above 0.60
acceptable threshold (Brace et al., 2009). Based on reliability and validity of the
Research Conclusions
245
measurement model verified in Chapter 7, Chapter 9 reports the tests of
hypotheses through regression and mediation analyses. For the regression
analyses, the study controls for gender, age, university type (whether public or
private university) and degree type (whether enrolled in a business degree or not).
The overall results show that the majority of the hypotheses are supported (S) at
either 1% or 5% level of significance with a few exceptions. Table 10.1 shows all
the hypotheses.
Table 10.132- Results of Hypotheses Testing
H1: Institutional factors are positively associated with feasibility and desirability of entrepreneurship
(B)
H1a: Regulatory institution is positively associated with feasibility S 0.070*
H1b: Regulatory institution is positively associated with desirability NS 0.054
H1c: Normative institution is positively associated with feasibility S 0.115**
H1d: Normative institution is positively associated with desirability S 0.130**
H1e: Cognitive institution is positively associated with feasibility S 0.118**
H1f: Cognitive institution is positively associated with desirability NS 0.016
H2: Individual factors are positively associated with feasibility and desirability of entrepreneurship
(B)
H2a: Risk taking propensity is positively associated with feasibility S 0.219**
H2b: Risk taking propensity is positively associated with desirability S 0.212**
H2c: Internal locus of control is positively associated with feasibility S 0.143**
H2d: Internal locus of control is positively associated with desirability S 0.133**
H2e: Need for achievement is positively associated with feasibility S 0.156**
H2f: Need for achievement is positively associated with desirability S 0.159**
H2g: Prior entrepreneurial exposure is positively associated with feasibility
S 0.289**
H2h: Prior entrepreneurial exposure is positively associated with desirability
S 0.111*
H3: Effectiveness of EE mediates the influence of institutional factors on feasibility and desirability of entrepreneurship
Indirect effect (ab)
H3a: Perceived learning mediates the relationship between regulatory institution and feasibility
S 0.037*
H3b: Perceived practical approaches mediate the relationship between regulatory institution and feasibility
S 0.046*
H3c: Perceived access to resources mediates the relationship between regulatory institution and feasibility
S 0.038*
H3d: Perceived learning mediates the relationship between regulatory institution and desirability
S 0.033*
H3e: Perceived practical approaches mediate the relationship between regulatory institution and desirability
S 0.035**
H3f: Perceived access to resources mediates the relationship between regulatory institution and desirability
S 0.021*
Research Conclusions
246
H3g: Perceived learning mediates the relationship between normative institution and feasibility
S 0.086**
H3h: Perceived practical approaches mediate the relationship between normative institution and feasibility
S 0.068**
H3i: Perceived access to resources mediates the relationship between normative institution and feasibility
S 0.063**
H3j: Perceived learning mediates the relationship between normative institution and desirability
S 0.075**
H3k: Perceived practical approaches mediate the relationship between normative institution and desirability
S 0.047**
H3l: Perceived access to resources mediates the relationship between normative institution and desirability
NS 0.022
H3m: Perceived learning mediates the relationship between cognitive institution and feasibility
S 0.041*
H3n: Perceived practical approaches mediate the relationship between cognitive institution and feasibility
S 0.054**
H3o: Perceived access to resources mediates the relationship between cognitive institution and feasibility
S 0.034*
H3p: Perceived learning mediates the relationship between cognitive institution and desirability
S 0.039*
H3q: Perceived practical approaches mediate the relationship between cognitive institution and desirability
S 0.047**
H3r: Perceived access to resources mediates the relationship between cognitive institution and desirability
S 0.019*
H4: EE mediates the effects of individual factors on feasibility and desirability of entrepreneurship
Indirect effect (ab)
H4a: Perceived learning mediates the relationship between risk taking propensity and feasibility
S 0.078**
H4b: Perceived practical approaches mediate the relationship between risk taking propensity and feasibility
S 0.046**
H4c: Perceived access to resources mediates the relationship between risk taking propensity and feasibility
S 0.053**
H4d: Perceived learning mediates the relationship between risk taking propensity and desirability
S 0.068**
H4e: Perceived practical approaches mediate the relationship between risk taking propensity and desirability
S 0.034**
H4f: Perceived access to resources mediates the relationship between risk taking propensity and desirability
NS 0.018
H4g: Perceived learning mediates the relationship between internal locus of control and feasibility
S 0.141**
H4h: Perceived practical approaches mediate the relationship between internal locus of control and feasibility
S 0.044**
H4i: Perceived access to resources mediates the relationship between internal locus of control and feasibility
S 0.051**
H4j: Perceived learning mediates the relationship between internal locus of control and desirability
S 0.120**
H4k: Perceived practical approaches mediate the relationship between internal locus of control and desirability
S 0.032*
H4l: Perceived access to resources mediates the relationship between internal locus of control and desirability
S 0.021*
Research Conclusions
247
H4m: Perceived learning mediates the relationship between need for achievement and feasibility
S 0.123**
H4n: Perceived practical approaches mediate the relationship between need for achievement and feasibility
S 0.045**
H4o: Perceived access to resources mediates the relationship between need for achievement and feasibility
S 0.049**
H4p: Perceived learning mediates the relationship between need for achievement and desirability
S 0.103**
H4q: Perceived practical approaches mediate the relationship between need for achievement and desirability
S 0.032**
H4r: Perceived access to resources mediates the relationship between need for achievement and desirability
S 0.017*
H4s: Perceived learning mediates the relationship between prior entrepreneurial exposure and feasibility
S 0.073**
H4t: Perceived practical approaches mediate the relationship between prior entrepreneurial exposure and feasibility
S 0.036*
H4u: Perceived access to resources mediates the relationship between prior entrepreneurial exposure and feasibility
S 0.034*
H4v: Perceived learning mediates the relationship between prior entrepreneurial exposure and desirability
S 0.068**
H4w: Perceived practical approaches mediate the relationship between prior entrepreneurial exposure and desirability
S 0.028*
H4x: Perceived access to resources mediates the relationship between prior entrepreneurial exposure and desirability
S 0.018*
H5: Perceived feasibility and desirability of entrepreneurship are positively associated with entrepreneurial intention
H5a: Perceived desirability of entrepreneurship is positively associated with entrepreneurial intention
S 0.472**
H5b: Perceived feasibility of entrepreneurship is positively associated with entrepreneurial intention
S 0.463**
Note: B is regression coefficient, ab is indirect effect, significance levels ** (1%), *(5%)
Note: S- Supported; and NS-Not Supported
Overall, the empirical evidence from both the qualitative research and quantitative
research has supported the basic EI model that EI is a function of perceptions of
feasibility and desirability of entrepreneurship, a perspective that is consistent with
prior research (Ajzen, 1991; Ajzen, 2011b; Fitzsimmons and Douglas, 2011;
Krueger JR et al., 2000; Liñán et al., 2011a; Shapero and Sokol, 1982).
Additionally, the results show that individual and institutional factors influence
perceived feasibility and desirability of entrepreneurship. More importantly, the
results indicate that effectiveness of EE significantly mediates the effects of
individual and institutional factors on perceived feasibility and desirability. This
means that individual and institutional factors exert their influence on perceived
Research Conclusions
248
feasibility and desirability in two ways: a) direct influence on perceived feasibility
and desirability; and b) indirect influence on perceived feasibility and desirability
via EE. Through appropriate pedagogical approaches, EE develops
entrepreneurial capabilities and clarifies the benefits of entrepreneurship.
Favourable institutions promote entrepreneurship by reducing barriers and
increasing awareness about the value and importance of entrepreneurship. Thus,
favourable institutions also drive people toward EE, affecting interest, attitude,
effort and the consequent performance in EE. This affects the level of
entrepreneurship knowledge and skills acquired through EE, which in turn
influences the perception that business start-up is worthwhile and possible.
Individuals differ in ability, temperament, personality, interests, and
upbringing/socialisation. Some factors on which individuals differ determine
whether one considers the tasks, roles, and activities of entrepreneurship to be
attractive and possible. Individuals with attributes important for entrepreneurship
not only find business start-up more attractive but also have more confidence in
venturing. Consequently, such individuals have more favourable predispositions
and interest toward EE. This affects effort and, hence, the level of
entrepreneurship knowledge and skills acquired through EE, which in turn
influences perceived feasibility and desirability of entrepreneurship.
10.2 Contributions to Knowledge
This research makes theoretical contributions along four directions. Firstly, against
the backdrop of mixed conclusions in prior research about the effect of EE on EI,
this study finds that the effect of EE should be examined in conjunction with
factors at individual and institutional levels. Specifically, it establishes that
effectiveness of EE mediates the effects of individual and institutional factors on
Research Conclusions
249
perceived feasibility and desirability of entrepreneurship i.e. the attitudinal
antecedents of EI. This helps clarify the role of EE. Secondly, unlike prior studies
and models that examine the influence of EE, individual factors and contextual
factors in isolation from each other, this study develops and validates a multi-level
integrated model to explore how these factors jointly shape EI. Thirdly, the study
confirms that the basic EI model is applicable in a developing country context.
Lastly, the research develops and validates constructs for assessing effectiveness
of EE.
10.2.1 The Intervening Role of EE
The first and most important contribution relates to the effect of EE on EI. The
extant literature has mixed conclusions; while some studies find that EE has
positive effects on EI, others report negative effects (Bae et al., 2014; Fayolle and
Liñán, 2014; Küttim et al., 2014). Because it is not yet clear if EE positively affects
EI and other entrepreneurial outcomes, scholars call for methodologically
adequate EE research as indicated in the quote below.
“Researchers have not yet answered the…relevant question as to what type of EE… for which type of student… under which sets of circumstances (or contexts) would positively affect entrepreneurial outcomes…We need a larger pool of methodologically adequate entrepreneurship education research. In this regard, well-designed cases studies would also be useful to help identify important mediators. We need more quantitative research that simultaneously examines the role of promising mediators like entrepreneurial self-efficacy, cognitive skills and knowledge, values and attitudes, social networks, and other contextual variables on policy relevant outcomes...” Rideout and Gray (2013, p.348)
In reponse to the foregoing inconclusive findings, this study empirically finds that
the effect of EE on EI should be evaluated in conjunction with factors at individual
and institutional levels. Specifically, the study demonstrates that effectiveness of
EE significantly mediates the effect of individual and institutional factors on
Research Conclusions
250
perceived feasibility and desirability of entrepreneurship. This means that
individual and institutional factors influence the uptake, interest, effort and the
consequent performance in EE to develop entrepreneurship knowledge and skills.
Entrepreneurship knowledge and skills in turn influence the perception that
starting, managing and growing a business is feasible and desirable. This
ultimately leads to EI.
10.2.2 Development and Validation of a Multi-level Model
The second contribution relates to the development and validation of a multi-level
conceptual model for EE and EI research. Prior research and the related
conceptual models explore the influences of EE, individual and contextual factors
on EI in isolation from each other (Fayolle and Liñán, 2014; Krueger, 2009;
Shepherd, 2011; Walter et al., 2011). This has prompted scholars to call for
models that help to examine how factors from the three angles are related in
shaping EI (De Clercq et al., 2011; Ertuna and Gurel, 2011; Fayolle and Liñán,
2014; Rideout and Gray, 2013; Solesvik et al., 2013). Scholars have argued that
focusing on only one angle often leads to incomplete understanding and
sometimes inconsistent conclusions (Cope, 2005; De Clercq et al., 2011; Dohse
and Walter, 2012; Fayolle and Liñán, 2014; Hitt et al., 2007; Krueger, 2009;
Rideout and Gray, 2013; Wang and Chugh, 2014).
“…the construct of intentions appears to be deeply fundamental to human decision making, and as such, it should afford us multiple fruitful opportunities to explore the connection between intent and a vast array of other theories and models that relate to decision making under risk and uncertainty. This view opens the door for the development of integrative and more sophisticated theoretical models of the entrepreneurial process… New research may consider interaction…moderation...and mediation effects.” Fayolle and Liñán (2014, p.664)
In response to the foregoing knowledge gap, the current study contributes to
knowledge by developing and empirically validating a multi-level conceptual
framework about the effect of EE on the relationships between EI and its
Research Conclusions
251
institutional and individual determinants (Figure 10.1). This model is unlike many
prior models that focus on one or two sets of factors.
Figure 10.115- Validated Conceptual Model for the Mediating Role of EE
The validated model demonstrates that individual and institutional factors exert
their effects on EI not only through their influence on perceived feasibility and
desirability but also through their influence on effectiveness of EE. By developing
entrepreneurial capabilities and clarifying the benefits of entrepreneurship, EE
enhances perceptions that business start-up is possible and valuable. In relation to
EI, the current research has identified that effectiveness of EE comprises
perceived learning from the module/programme, utilisation of resources and
experiential learning. Individual factors consist of risk taking propensity, locus of
control, need for achievement, and prior entrepreneurial exposure. Lastly,
institutional factors comprise normative, cognitive and regulatory institutions. The
study finds that individual and institutional factors are the primary predictors of
perceived feasibility and desirability of entrepreneurship. The role of EE is to
mediate these relationships. This ultimately leads to EI.
Research Conclusions
252
In relation to the validity of the proposed conceptual model, extant literarure
indicates that combinations of positivistic research (addressing ‘what’ issues) and
interpretivistic research (addressing the ‘how’ and “why” issues) are rare and yet
important for model testing and comprehensive understanding of phenomena
(Fayolle and Liñán, 2014; Gartner, 2010; Molina-Azorín et al., 2012; Shook et al.,
2003; Stevenson and Jarillo, 1990; van Burg and Romme, 2014). Such a strategy
is especially important in this area, where conclusions in prior research are
contradictory to each other. Such a strategy is also important because the study is
conducted in the context of an under-researched developing country. The fact that
there is convergence between qualitative and quantitative research findings in this
research indicates the validity of the research design and the value of the
established model.
10.2.3 Applying the EI Model in a Developing Country Context
The third contribution relates to contextual applicability of the basic EI model. The
findings confirm the propositions from the theory of planned behaviour (TPB) and
Shapero’s entrepreneurial event (SEE) model that EI is primarily a function of
perceived feasibility and desirability of entrepreneurship (Ajzen, 1991; Ajzen,
2011b; Fitzsimmons and Douglas, 2011; Krueger JR et al., 2000; Liñán et al.,
2011a; Schlaegel and Koenig, 2014; Shapero and Sokol, 1982). Scholars indicate
that generally most studies in entrepreneurship, graduate entrepreneurship and EI
in particular, are conducted in developed countries and this limits generalisability
of the findings elsewhere (Fayolle and Liñán, 2014; Hoskisson et al., 2011; Nabi
and Liñán, 2011; Solesvik et al., 2013). The consequence of scant research in
developing countries is that researchers, policy makers, educators and other
stakeholders do not have adequate information that takes into account local
contexts for research, practice and policy direction. By conducting the research in
Research Conclusions
253
Zambia, the study confirms the applicability of the basic EI model as well as the
influences of institutional factors, individual factors and EE on EI in a developing
country context.
10.2.4 Further Development/Validation of Effectiveness of EE Constructs
The fourth contribution is the development and validation of the constructs of
effectiveness of EE. Extant literature indicates that the link between pedagogical
approaches and EI is not clear (De Grez and Van Lindt, 2012; Fayolle and Liñán,
2014; Krueger Jr, 2009; Küttim et al., 2014). In this regard, scholars indicate that
“clearly there is also need for development of pyschometrically sound measures to
support efforts in…entrepreneurship education research” (Rideout and Gray,
2013, p.348). In the literature, only Souitaris et al.(2007) developed and validated
constructs of effectiveness of EE, based on perceived learning and utilisation of
resources. The present study adopted and further validated the constructs from
Souitaris et al.(2007). Furthermore, the study developed and validated the
construct for perceived experiential learning (practical approaches). This allows
the measurement of effectiveness of EE to go beyond the education content (i.e.
learning from the module) and include experiential learning (i.e learning by doing).
In relation to the link between pedagogical approaches and EI, this study has
found that experiential learning is positively associated with feasibility and
desirability of entrepreneurship. Validated constructs for evaluation of the
effectiveness of EE may be the basis for identifying and improving specific aspects
of the EE offering. This is especially important because EE delivery is widely
criticised for being dominated by lectures and seminars; EE delivery should
include experiential learning, networking and coaching activities.
Research Conclusions
254
10.3 Implications to Policy and Practice
The findings have implications for policy makers and practitioners in
entrepreneurship education (EE) and entrepreneurship support organisations.
10.3.1 Implications to Policy Makers
From a policy perspective, to increase graduate’s involvement in new venture
creation, there is need for a holistic and multifaceted approach. Specifically,
coordinated policies/strategies/programmes are required to promote EE,
entrepreneurship training as well as favourable regulatory, cognitive and normative
institutions for entrepreneurship. This is because EE may not lead to business
start-up if potential entrepreneurs perceive insurmountable challenges in the
entrepreneurial environment. Favourable regulatory mechanisms should include
easy access to finance, sustained business advisory and training services,
simplified regulations on business operations, lower formalisation costs, access to
markets as well as affordable relevant infrastructure and technology. The
availability of favourable mechanisms may encourage more individuals to set up
businesses. However, even when regulatory institutions are favourable, not
everyone will start a business. Personal issues such as willingness and readiness
to bear risks, prior entrepreneurial exposure as well as entrepreneurial and
technical skills can all influence business creation.
Favourable normative institutions entail society’s admiration of entrepreneurship,
innovation and creativity. This not only promotes the status of entrepreneurship in
society but also increases the likelihood of moral, emotional, regulatory and
material support from other stakeholders such as family, peers, colleagues, policy
makers, relevant public and private organisations. To achieve this, multifaceted
inputs are required from the media, government and non-government enterprise
support organisations, role models as well as schools. Furthermore, favourable
Research Conclusions
255
cognitive institution helps increase people’s understanding of what is involved in
entrepreneurship. Consequently, it not only influences potential entrepreneurs’
confidence in their abilities to start and manage a business but it also promotes
the status of entrepreneurship.
Government could develop and implement coordinated nationwide policies and
strategies to promote start-up and SME growth. Such policies and strategies
should address concerted collaborative mechanisms amongst higher education
institutions, government and non-government entrepreneurship support agencies,
business regulatory and registration authorities and local authorities to promote
entrepreneurship (CBI - NUS, 2011; Consultants, 2008; Gibcus et al., 2012; Lord
Young, 2012; Lord Young, 2013; Rae, 2007a; Rae, 2010; Rae et al., 2012; Small
Business Charter, 2014; Witty, 2013). Specifically, EE should be embedded in
curriculum and extra-curriculum in institutions of learning. Periodically the
implementation of EE and support mechanisms could be monitored and evaluated
so that best practices are promoted and shared. The findings also suggest that
decentralised mechanisms for government and non-government financial and
regulatory support to start-ups and SMEs would be more effective. In addition,
there is need for policy makers to work with local authorities that may be better
placed to provide infrastructure support such as incubators and other start-up
incentives. For effectiveness, annual targets for a manageable number of fledgling
businesses to be supported should be set.
Since starting any business is fraught with uncertainty, financial burdens and
resource constraints, business incubator (BI) services would provide a nurturing,
instructive and supportive environment for some entrepreneurs during the first
critical stages i.e. 3 years (Bruneel et al., 2012; CABI, 2014; NBIA, 2014; UKBI,
2014). The goal of BIs is usually to increase the chance that a start-up will
Research Conclusions
256
succeed, achieve growth, shorten the time and reduce the cost of getting
established. The graduating firm should leave the programme financially viable
and free standing (CABI, 2014; Clarysse et al., 2005; Mutambi et al., 2010; Phan
et al., 2005; Ratinho and Henriques, 2010). To achieve their objectives, BIs
typically provide their clients (or tenants) with a mix of services encompassing
infrastructure, business support services and networking (Bergek and Norrman,
2008; Bruneel et al., 2012; Lalkaka, 2009).
10.3.2 Implications to Practice
Further to the foregoing policy implications, the findings have implications for EE
practice and entrepreneurship support. For entrepreneurship support practitioners,
the study implies that there is need to efficiently and effectively disseminate
information on available regulatory and other support mechanisms to relevant
stakeholders. This is necessary to enable potential and nascent entrepreneurs
inside and outside learning institutions to thoroughly understand the available
institutional support and how to access it. For effectiveness, collaborative
mechanisms may be required to coordinate efforts of stakeholders such as banks,
role model entrepreneurs, educators, local authorities and enterprise support
practitioners to deliver training, mentoring and coaching through workshops,
incubators/science parks and EE channels for potential and nascent entrepreneurs
inside and outside universities.
To contribute to new venture creation, EE offering should focus on content and
methods of delivery which allow participants to engage in activities that enable one
to understand the entrepreneurial process and its behavioural requirements.
Participants should also learn not only how to harness the available support but
also how to overcome some of the challenges in the environment. To participate
as decentralised conduits of start-up and SME growth support, higher education
Research Conclusions
257
institutions may be required to initiate and grow in provision of the following
services (CBI - NUS, 2011; Consultants, 2008; Gibcus et al., 2012; Lord Young,
2012; Lord Young, 2013; Rae, 2007a; Rae, 2010; Rae et al., 2012; Small
Business Charter, 2014; Witty, 2013): a) graduate/student start‐up and
employability support; b) start-up and small business growth support; c) wider
stakeholder engagement in SME growth issues.
10.4 Limitations and Recommendations for Future Research
10.4.1 Research Limitations
All research has limitations and this study is of no exception. Firstly, this study is
cross-sectional and, therefore, the findings may be time specific and lack
generalisability over time.
The second limitation is in relation to research context. The study used empirical
data from a single developing country and, thus, the findings may be limited to
Zambia and not generalisable to other countries in the region and beyond (Fayolle
and Liñán, 2014; Hoskisson et al., 2011).
The third limitation relates to data analyses. The advantage of using structural
equation modelling (SEM) technique is that instead of assuming that equations
generating direct and indirect paths (i.e. paths a, b, c’ and c) are independent, it
estimates everything simultaneously. In this study, the multiple independent and
multiple mediator variables meant that the hierarchical multiple regression format
examined each relationship in the model separately. While models with many
mediation pathways become tortuous and complicated, simultaneously assessing
the effects of many variables in a model approximates reality closer (Hayes, 2013;
Jose, 2013; Zhao et al., 2010b). However, it should be noted that the conceptual
issues in mediation analysis hold with equal force to SEM and regression analyses
Research Conclusions
258
i.e. whether via regression or SEM, only the indirect effect needs to be significant
(Zhao et al, 2010b; Naylor et al., 2012).
10.4.2 Directions for Future Research
In light of the findings and limitations of the research, directions for future research
are suggested. First, future studies may consider employing a longitudinal
research design to evaluate the veracity of the model on the intervening role of EE
on EI over time. For instance, studies could compare EE participants and non-
participants before and after the educational intervention. This would allow for the
intervening role of EE to be assessed over time. It would also allow for causality to
be inferred. Even cross sectional studies could consider controlling for pre-EE EI.
Second, studies could assess EI and the transition into actual venture creation
based on the duration and characteristics of EE. For instance, samples of
participants in short and long EE programmes could be compared. The
comparison could be done at the beginning, end of the programmes and even
beyond. This would enable scholars to understand the impact of duration of EE on
EI and actual entrepreneurial behaviour over time.
Third, future studies could further test the veracity of the model in different
contexts. For example, samples from two or more countries at the same or
different levels of economic development could be compared. Also individuals
receiving entrepreneurial training outside institutions of higher education could be
sampled. This would enable scholars to assess the generalisability of the model in
different contexts and countries.
Fourth, future studies could explore interacting effects among EI determinants. For
instance, among institutional factors, future studies could explore if there are
interactions amongst cognitive, normative and regulatory institutions. This may
Research Conclusions
259
enhance readers’ understanding of how the effect of one factor on EI changes in
the absence or presence of one or more of the other factors (Fayolle and Liñán,
2014; Fitzsimmons and Douglas, 2011).
Fifth, future studies should note that while literature recommends use of validated
constructs from high quality prior studies, the constructs avalaible may have
implicit problems. For instance, in this study a few items comprising constructs for
the normative institution, regulatory institution and practical approaches to EE
delivery may have a double or triple barrel problem that would potentially influence
the findings. Although in this research each respondent at the start and end of
answering the survey questionnare was asked to indicate if any of the questions
was unclear, more caution is recommended when adopting and adapting existing
constructs in future.
Sixth, future studies should consider including other factors at individual and
institutional levels to explore their effects on the effectiveness of EE. For example,
among background factors, researchers could consider assessing the impact of
the possibility that some students are advised by parents or influenced by their
friends to pursue entrepreneurship programmes. This would be in line with Ajzen’s
(1991) theory of planned behaviour concept of subjective norms i.e. whether
parents, relatives, friends and colleagues’ approval or disapproval of a particular
behaviour impacts the adoption of that behaviour. Among contextual factors,
differences in religion and ethnicity could also be considered.
Lastly, future studies could use structural equation modelling (SEM) to explore
how the model would be pruned and what additional insights could emerge from a
simultaneous interplay of individual factors, institutional factors and EE’s effects on
EI. While models with many mediation pathways become tortuous and
Research Conclusions
260
complicated, simultaneously assessing the effects of many variables in a model
approximates reality closer (Hayes, 2013; Jose, 2013; Zhao et al., 2010b).
10.5 Final Conclusion
The extant literature shows that entrepreneurship contributes to economic
development, competition, innovation and job creation for economies. Given its
contribution to the economy, the changing employer expectations and the
increasing problem of graduate unemployment, there is growing need to
understand the factors that contribute to increasing entrepreneurship. EI is critical
in the entrepreneurial process since empirical evidence shows that individuals with
EI are more likely to start their own businesses (Bird, 1988; Bird, 1992; Henley,
2007; Kautonen et al., 2013). The small but growing body of literature on the
influence of EE on EI shows that findings are sometimes contradictory to each
other. Apart from scarcity of studies from developing countries on EE and EI, there
is a shortage of studies investigating whether EE has an impact on relationships
between EI and its individual and institutional determinants (Rideout and Gray,
2013; De Clercq et al., 2011; Ertuna and Gurel, 2011; Krueger, 2009; Fayolle and
Liñán, 2014). Furthermore, research on the influence of EE, individual and
institutional factors on EI has grown in isolation from each other (Fayolle and
Liñán, 2014). There is also a shortage of empirical studies investigating the
influence of country institutional profile of entrepreneurship on EI (Bruton et al.,
2010; De Clercq et al., 2011; Engle et al., 2011).
Responding to the foregoing knowledge gaps, and through a concurrent
triangulation research strategy, this study has developed and validated a
conceptual model showing that the effect of EE on EI should be evaluated in
conjunction with individual and institutional factors. Firstly, EI is primarily a function
Research Conclusions
261
of perceived feasibility and desirability of entrepreneurship. Secondly, individual
and institutional factors influence perceived feasibility and desirability of
entrepreneurship in two ways: directly and indirectly via EE. Lastly, the findings
derived suggest that, in order to promote graduate entrepreneurship, multifaceted
and concerted efforts will be required from policy makers (to help shape
institutions), practitioners (to devise and implement collaborative support
mechanisms), educators (to design and deliver appropriate EE content and
pedagogy) and scholars (to evaluate and develop knowledge).
262
REFERENCES
Aarts, H., Dijksterhuis, A., 2000. Habits as Knowledge Structures: Automaticity in Goal-Directed Behavior. Journal of Personality and Social Psychology 78 (1), 53.
Acs, Z., 2006. How is Entrepreneurship Good for Economic Growth? Innovations: Technology, Governance, Globalization 1 (1), 97-107.
Acs, Z., Szerb, L., 2012. Global Entrepreneurship and Development Index 2012. Edward Elgar Pub.
African Economic Outlook, 2014. Economic Outlook of Zambia, http://www.africaneconomicoutlook.org/en/countries/southern-africa/zambia/ accessed July 14, 2014 10:00 Hours UK Time.
Agbor, J., Taiwo, O., Smith, J., 2012. Sub-Saharan Africa’s Youth Bulge: A Demographic Dividend Or Disaster, Foresight Africa: Top Priorities for the Continent in 2012 The Brookings Institution, Africa Growth Initiative, 9-11.
Ahmad, H.M., 2010. Personality Traits among Entrepreneurial and Professional CEO's in SMEs, International Journal of Business and Management 5 (9), P203.
Ahmed, S.U., 1985. nAch, Risk-Taking Propensity, Locus of Control and Entrepreneurship, Personality and Individual Differences 6 (6), 781-782.
Ainuddin, R.A., Junit, S.H., Poon, J.M.L., 2006. Effects of Self-Concept Traits and Entrepreneurial Orientation on Firm Performance, International Small Business Journal 24, 61+.
Ajzen, I., 2002. Perceived Behavioral Control, Self‐Efficacy, Locus of Control, and the Theory of Planned Behavior, Journal of Applied Social Psychology 32 (4), 665-683.
Ajzen, I., 1991. The Theory of Planned Behavior, Organizational Behavior and Human Decision Processes 50 (2), 179-211.
Ajzen, I., Fishbein, M., 2005. The Influence of Attitudes on Behavior, The Handbook of Attitudes 173, 221.
Ajzen, I., Fishbein, M., 1980. Understanding Attitudes and Predicting Social Behavior. Prentice-Hall.
Ajzen, I., 2011a. Constructing a Theory of Planned Behavior Questionnaire, Unpublished Manuscript.Retrieved 1.
Ajzen, I., 2011b. The Theory of Planned Behaviour: Reactions and Reflections, Psychology & Health 26 (9), 1113-1127.
Allinson, C.W., Chell, E., Hayes, J., 2000. Intuition and Entrepreneurial Behaviour, European Journal of Work and Organizational Psychology 9 (1), 31-43.
Almobaireek, W.N., Manolova, T.S., 2012. Who Wants to be an Entrepreneur? Entrepreneurial Intentions among Saudi University Students, African Journal of Business Management 6 (11), 4029-4040.
Altinay, L., Madanoglu, M., Daniele, R., Lashley, C., 2012. The Influence of Family Tradition and Psychological Traits on Entrepreneurial Intention, International Journal of Hospitality Management 31 (2), 489-499.
Alvarez, C., Urbano, D., Coduras, A., Ruiz-Navarro, J., 2011. Environmental Conditions and Entrepreneurial Activity: A Regional Comparison in Spain, Journal of Small Business and Enterprise Development 18 (1), 120-140.
Alvarez, S.A., Busenitz, L.W., 2001. The Entrepreneurship of Resource-Based Theory, Journal of Management 27 (6), 755-775.
Andrew C., C., 2007. Learning Asymmetries and the Discovery of Entrepreneurial Opportunities, Journal of Business Venturing 22 (1), 97-118.
Andrews, F.M., Robinson, J.P., Shaver, P.R., Wrightsman, L.S., 1991. Measures of Personality and Social Psychological Attitudes. Access Online via Elsevier.
Andrews, K., 1971. Concept of Corporate Strategy Aouni, Z., Pirnay, F., 2009. L’impact De L’exposition À Des Modèles D’entrepreneurs Sur
Les Antécédents De L’intention Entrepreneuriale, Actes Du 6ème Congrès De l’Académie De L’Entrepreneuriat.
Arabsheibani, G., De Meza, D., Maloney, J., Pearson, B., 2000. And a Vision Appeared Unto them of a Great Profit: Evidence of Self-Deception among the Self-Employed, Economics Letters 67 (1), 35-41.
263
Arasti, Z., Kiani Falavarjani, M., Imanipour, N., 2012. A Study of Teaching Methods in Entrepreneurship Education for Graduate Students, Higher Education Studies 2 (1), p2.
Arenius, P., Clercq, D.D., 2005. A Network-Based Approach on Opportunity Recognition, Small Business Economics 24 (3), 249-265.
Aronsson, M., 2004. Education Matters--but does Entrepreneurship Education? an Interview with David Birch, Academy of Management Learning & Education 3 (3), 289-292.
Atherton, A., 2004. Unbundling Enterprise and Entrepreneurship: From Perceptions and Preconceptions to Concept and Practice, The International Journal of Entrepreneurship and Innovation 5 (2), 121-127.
Atkinson, R., Atkinson, K., Hilgard, E., 1983. Introduction to Psychology. Audretsch, D.B., 2007. Entrepreneurship Capital and Economic Growth, Oxford Review of
Economic Policy 23 (1), 63-78. Audretsch, D.B., Acs, Z.J., 1994. New-Firm Startups, Technology, and Macroeconomic
Fluctuations, Small Business Economics 6 (6), 439-449. Autio, E., Keeley, R.H., Klofsten, M., Parker, G.G.C., Hay, M., 2001. Entrepreneurial Intent
among Students in Scandinavia and in the USA, Enterprise and Innovation Management Studies 2 (2), 145-160.
Babb, E.M., Babb, S.V., 1992. Psychological Traits of Rural Entrepreneurs, Journal of Socio-Economics 21 (4), 353-362.
Bae, T.J., Qian, S., Miao, C., Fiet, J.O., 2014. The Relationship between Entrepreneurship Education and Entrepreneurial Intentions: A Meta-Analytic Review, Entrepreneurship Theory and Practice 38 (2), 217-254.
Bagozzi, R.P., Yi, Y., 1991. Multitrait-Multimethod Matrices in Consumer Research, Journal of Consumer Research, 426-439.
Bagozzi, R.P., Yi, Y., Phillips, L.W., 1991. Assessing Construct Validity in Organizational Research, Administrative Science Quarterly, 421-458.
Baker, M.J., 2003. Qualitative Market Research: Principles and Practice, Journal of Marketing Management 19 (3), 515-516.
Bandura, A., 1993. Perceived Self-Efficacy in Cognitive Development and Functioning, Educational Psychologist 28 (2), 117-148.
Bandura, A., 1982. Self-Efficacy Mechanism in Human Agency. American Psychologist 37 (2), 122.
Bandura, A., 2001. Social Cognitive Theory: An Agentic Perspective, Annual Review of Psychology 52, 1-26.
Bandura, A., 1977. Self-Efficacy: Toward a Unifying Theory of Behavioral Change, Psychological Review 84 (2), 191-215.
Bandura, Albert, 1989. Regulation of Cognitive Processes through Perceived Self-Efficacy, Developmental Psychology 25 (5), 729-735.
Bank of Zambia, 2014. Country Data for Zambia, http://www.boz.zm/ accessed July 13, 2014 18:00 Hours UK Time.
Bank of Zambia FinScope, 2010. A Survey of the Population's Access to Financial Access in Zambia, Bank of Zambia Website Access March 20, 2014 16:00 Hours UK Time.
BarNir, A., Watson, W.E., Hutchins, H.M., 2011. Mediation and Moderated Mediation in the Relationship among Role Models, Self‐Efficacy, Entrepreneurial Career Intention, and Gender, Journal of Applied Social Psychology 41 (2), 270-297.
Baron, R.A., 2000. Counterfactual Thinking and Venture Formation: The Potential Effects of Thinking About, Journal of Business Venturing 15 (1), 79-91.
Baron, R.M., Kenny, D.A., 1986. The Moderator–mediator Variable Distinction in Social Psychological Research: Conceptual, Strategic, and Statistical Considerations. Journal of Personality and Social Psychology 51 (6), 1173.
Baron, R.A., Ensley, M.D., 2006. Opportunity Recognition as the Detection of Meaningful Patterns: Evidence from Comparisons of Novice and Experienced Entrepreneurs, Management Science 52 (9), 1331-1344.
Barrick, M.R., Mount, M.K., 1991. The Big Five Personality Dimensions and Job Performance: A Meta‐analysis, Personnel Psychology 44 (1), 1-26.
264
Bartlett, M.S., 1954. A Note on the Multiplying Factors for various Χ 2 Approximations, Journal of the Royal Statistical Society.Series B (Methodological), 296-298.
Bateman, T.S., Zeithaml, C.P., 1989. The Psychological Context of Strategic Decisions: A Model and Convergent Experimental Findings, Strategic Management Journal 10 (1), 59-74.
Baughn, C.C., Cao, J.S.R., Le, L.T.M., Lim, V.A., Neupert, K.E., 2006. Normative, Social and Cognitive Predictors of Entrepreneurial Interest in China, Vietnam and the Philippines, Journal of Developmental Entrepreneurship 11 (1), 57.
Baumol, W.J., 1993. Formal Entrepreneurship Theory in Economics: Existence and Bounds, Journal of Business Venturing 8 (3), 197-210.
Baumol, W., Litan, R., Schramm, C., 2007. Good Capitalism, Bad Capitalism, and the Economics of Growth and Prosperity, Bad Capitalism, and the Economics of Growth and Prosperity.
Béchard, J., Grégoire, D., 2005. Entrepreneurship Education Research Revisited: The Case of Higher Education, Academy of Management Learning & Education 4 (1), 22-43.
Becker, G.S., 2009. Human Capital: A Theoretical and Empirical Analysis, with Special Reference to Education. University of Chicago Press.
Becker, G.S., 1962. Investment in Human Capital: A Theoretical Analysis, The Journal of Political Economy, 9-49.
Beeka, B.H., Rimmington, M., 2011. Entrepreneurship as A Career Option for African Youths, Journal of Developmental Entrepreneurship 16 (01), 145-164.
Begley, T.M., Boyd, D.P., 1986. Psychological Characteristics Associated with Entrepreneurial Performance, Frontiers of Entrepreneurship Research 146.
Bergek, A., Norrman, C., 2008. Incubator Best Practice: A Framework, Technovation 28 (1), 20-28.
Bhaskar, R., 2008. A Realist Theory of Science. Taylor & Francis US. Bhaskar, R., 1998. Philosophy and Scientific Realism, Critical Realism: Essential
Readings, 16-47. Bhaskar, R., 1978a. On the Possibility of Social Scientific Knowledge and the Limits of
Naturalism, Journal for the Theory of Social Behaviour 8 (1), 1-28. Bhaskar, R., 1978b. A Realist Philosophy of Science, Harvester Wheatsheaf, Hemel
Hempstead. Bhide, A., 2000. The Origin and Evolution of New Businesses. Oxford University Press,
USA. Bianchi, M., 2010. Credit Constraints, Entrepreneurial Talent, and Economic
Development, Small Business Economics 34 (1), 93-104. Birch, D., 1979. The Job Generation Process, University of Illinois at Urbana-Champaign's
Academy for Entrepreneurial Leadership Historical Research Reference in Entrepreneurship.
Bird, B., 1988. Implementing Entrepreneurial Ideas: The Case for Intention, Academy of Management Review 13 (3), 442-453.
Bird, B.J., 1992. The Operation of Intentions in Time: The Emergence of the New Venture, Entrepreneurship: Theory & Practice 17 (1), 11-20.
Birdthistle, N., 2008. An Examination of Tertiary Students' Desire to found an Enterprise, Education Training 50 (7), 552-567.
Blanchflower, D., Shadforth, C., 2007. Entrepreneurship in the UK, Foundations and Trends in Entrepreneurship 3 (4), 257-364.
Blenker, P., Korsgaard, S., Neergaard, H., Thrane, C., 2011. The Questions we Care about: Paradigms and Progression in Entrepreneurship Education, Industry and Higher Education 25 (6), 417-427.
Blickle, G., 1996. Personality Traits, Learning Stratigies, and Performance, European Journal of Personality 10 (5), 337-352.
Block, Z., Stumpf, S.A., 1990. Entrepreneurship Education Research: Experience and Challenge. Center for Entrepreneurial Studies, New York University, Leonard N. Stern School of Business.
Blumer, H., 1986. Symbolic Interactionism: Perspective and Method. University of California Press.
265
Blumer, H., 1966. Sociological Implications of the Thought of George Herbert Mead. Blundel, R., 2007. Critical Realism: A Suitable Vehicle for Entrepreneurship Research,
Handbook of Qualitative Research Methods in Entrepreneurship, 49-78. Bogdan, R., Taylor, S.J., 1975. Introduction to Qualitative Methods: A Phenomenological
Approach to the Social Sciences. Boissin, J., Emin, S., 2007. Les Étudiants Et L'Entrepreuneuriat: L'Effet Des Formations,
Gestion 2000, 24 (3,). Bolton, B., Thompson, J., 2002. The Entrepreneur in Focus: Achieve Your Potential.
Cengage Learning EMEA. Bonchek, M.S., ShepSle, K.A., 1997. Analyzing Politics: Rationality, Behaviour and
Institutions, . Bonnett, C., Furnham, A., 1991. Who Wants to be an Entrepreneur? A Study of
Adolescents Interested in a Young Enterprise Scheme, Journal of Economic Psychology 12 (3), 465-478.
Bono, J.E., McNamara, G., 2011. Publishing in AMJ—Part 2: Research Design, Academy
of Management Journal 54 (4), 657-660. Bontempo, R., Rivero, J., 1992. Cultural Variation in Cognition: The Role of Self-Concept
in the Attitude-Behavior Link. In: Meeting of the American Academy of Management, Las Vegas, Nevada.
Bosma, N., Van Praag, M., Thurik, R., De Wit, G., 2004. The Value of Human and Social Capital Investments for the Business Performance of Startups, Small Business Economics 23 (3), 227-236.
Bouchard, T.J., 1976. Unobtrusive Measures an I Nventory of Uses, Sociological Methods & Research 4 (3), 267-300.
Bowen, H.P., De Clercq, D., 2007. Institutional Context and the Allocation of Entrepreneurial Effort, Journal of International Business Studies 39 (4), 747-767.
Boyd, N.G., Vozikis, G.S., 1994. The Influence of Self-Efficacy on the Development of Entrepreneurial Intentions and Actions, Entrepreneurship: Theory & Practice 18 (4), 63-77.
Brace, N., Kemp, R., Snelgar, R., 2009. SPSS for Psychologists. Palgrave Macmillan Hampshire.
Brandstätter, V., Lengfelder, A., Gollwitzer, P.M., 2001. Implementation Intentions and Efficient Action Initiation. Journal of Personality and Social Psychology 81 (5), 946.
Brännback, M., Carsrud, A., Elfving, J., Kickul, J., Krueger, N., 2006. Why Replicate Entrepreneurial Intentionality Studies? Prospects, Perils, and Academic Reality. In: SMU Edge Conference, Singapore.
Breiman, L., 1992. The Little Bootstrap and Other Methods for Dimensionality Selection in Regression: X-Fixed Prediction Error, Journal of the American Statistical Association 87 (419), 738-754.
Bremmer, I., 2009. State Capitalism Comes of Age: The End of the Free Market? Foreign Affairs , 40-55.
Bridge, S., O'Neill, K., Martin, F., Cromie, S., 2009. Understanding Enterprise: Entrepreneurship and Small Business. Palgrave Macmillan.
Brockhaus Sr, R.H., 1980. Risk Taking Propensity of Entrepreneurs, Academy of Management Journal, 509-520.
Brockhaus, R.H., 2001. Entrepreneurship Education: A Global View. Ashgate. Brockhaus, R.H., Horwitz, P.S., 1982. The Psychology of the Entrepreneur, Encyclopedia
of Entrepreneurship 39, 71. Brockhaus, R.H., Nord, W.R., 1979. An Exploration of Factors Affecting the
Entrepreneurial Decision: Personal Characteristics Vs. Environmental Conditions, Proceedings of the National Academy of Management 39, 364-368.
Brockhaus, R.H., Horwitz, P., 1986. The Psychology of the Entrepreneur, 1996) Entrepreneurship: Critical Perspectives on Business and Management 2, 260-283.
Brodsky, M.A., 1993. Successful Female Corporate Managers and Entrepreneurs, Group & Organization Management 18 (3), 366.
Bruneel, J., Ratinho, T., Clarysse, B., Groen, A., 2012. The Evolution of Business Incubators: Comparing Demand and Supply of Business Incubation Services Across Different Incubator Generations, Technovation 32 (2), 110-121.
266
Bruton, G.D., Ahlstrom, D., Han-Lin Li, 2010. Institutional Theory and Entrepreneurship: Where are we Now and Where do we Need to Move in the Future? Entrepreneurship: Theory & Practice 34 (3), 421-440.
Bruton, G.D., Ahlstrom, D., Obloj, K., 2008. Entrepreneurship in Emerging Economies: Where are we Today and Where should the Research Go in the Future, Entrepreneurship Theory and Practice 32 (1), 1-14.
Bruyat, C., Julien, P., 2001. Defining the Field of Research in Entrepreneurship, Journal of Business Venturing 16 (2), 165-180.
Bryman, A., Bell, E., 2011. Business Research Methods. Oxford University Press, Oxford. Buchanan, D., Boddy, D., McCalman, J., 1986. Getting in, Getting on, Getting Out, Getting
Back. University of Glasgow Department of Management Studies. Buchanan, D., Bryman, A., 2009. The SAGE Handbook of Organizational Research
Methods. Sage Publications Ltd. Burke, A.E., FitzRoy, F.R., Nolan, M.A., 2000. When Less is More: Distinguishing
between Entrepreneurial Choice and Performance, Oxford Bulletin of Economics and Statistics 62 (5), 565-587.
Burns, R.B., Burns, R.A., 2008. Business Research Methods and Statistics using SPSS. SAGE Publications Ltd.
Burrell, G., Morgan, G., 1979. Sociological Paradigms and Organisational Analysis: Elements of the Sociology of Corporate Life.
Busenitz, L.W., 1999. Entrepreneurial Risk and Strategic Decision Making, The Journal of Applied Behavioral Science 35 (3), 325-340.
Busenitz, L.W., Barney, J.B., 1997. Differences between Entrepreneurs and Managers in Large Organizations: Biases and Heuristics in Strategic Decision-Making, Journal of Business Venturing 12 (1), 9-30.
Busenitz, L.W., Gómez, C., Spencer, J.W., 2000. Country Institutional Profiles: Unlocking Entrepreneurial Phenomena, Academy of Management Journal 43 (5), 994-1003.
Busenitz, L.W., Lau, C.M., 1996. A Cross-Cultural Cognitive Model of New Venture Creation, Entrepreneurship Theory and Practice 20, 25-40.
Business, D., 2010. Doing Business 2011: Making a Difference for Entrepreneurs, Washington: The World Bank.
Byabashaija, W., Katono, I., 2011. The Impact of College Entrepreneurial Education on Entrepreneurial Attitudes and Intention to Start a Business in Uganda, Journal of Developmental Entrepreneurship (JDE) 16 (01), 127-144.
Bygrave, W.D., Hofer, C.W., 1991. Theorizing about Entrepreneurship, Entrepreneurship: Theory and Practice 16 (2), 13-22.
Bygrave, W.D., 1989. The Entrepreneurship Paradigm (I): A Philosophical Look at its Research Methodologies, Entrepreneurship: Theory & Practice 14 (1), 7-26.
CABI, 2014. Canadian Association of Business Incubation, http://www.cabi.ca/business-incubation.php accessed on 20.04.2014.
Caird, S., 1991. Testing Enterprising Tendency in Occupational Groups, British Journal of Management 2 (4), 177.
Calice, P., Chando, V.M., Sekioua, S., 2012. Bank Financing to Small and Medium Enterprises in East Africa: Findings of a Survey in Kenya, Tanzania, Uganda and Zambia.
Caliendo, M., 2013. Endogeneity in Entrepreneurship Research, Applied Econometrics Research Seminar Paper, University of Potsdam
Campbell, D.T., Fiske, D.W., 1959. Convergent and Discriminant Validation by the Multitrait-Multimethod Matrix. Psychological Bulletin 56 (2), 81.
Cantillon, R., 2010. Essay on Economic Theory, An. English Translation of the 1755 French Essay by Saucier C. and Edited by Thornton M. Published by The Ludwig von Mises Institute.
Cantillon, R., 1755. Essay on the Nature of General Commerce. Carland, J.W., Hoy, F., Boulton, W.R., Carland, J.A.C., 1984. Differentiating
Entrepreneurs from Small Business Owners: A Conceptualization, Academy of Management Review, 354-359.
267
Carr, J.C., Sequeira, J.M., 2007. Prior Family Business Exposure as Intergenerational Influence and Entrepreneurial Intent: A Theory of Planned Behavior Approach, Journal of Business Research 60 (10), 1090-1098.
Carree, M., Van Stel, A., Thurik, R., Wennekers, S., 2002. Economic Development and Business Ownership: An Analysis using Data of 23 OECD Countries in the Period 1976–1996, Small Business Economics 19 (3), 271-290.
Carree, M.A., Thurik, A.R., 2010. The Impact of Entrepreneurship on Economic Growth, Handbook of Entrepreneurship Research, 557-594.
Carter, N.M., Gartner, W.B., Reynolds, P.D., 1996. Exploring Start-Up Event Sequences, Journal of Business Venturing 11 (3), 151-166.
Carter, N.M., Gartner, W.B., Shaver, K.G., Gatewood, E.J., 2003. The Career Reasons of Nascent Entrepreneurs, Journal of Business Venturing 18 (1), 13-39.
Cassidy, T., Lynn, R., 1989. A Multifactorial Approach to Achievement Motivation: The Development of a Comprehensive Measure. Journal of Occupational Psychology.
Casson, M., 1995. Entrepreneurship and Business Culture (Studies in the Economics of Trust)(V. 1). Edward Elgar, Aldershot.
Casson, M., 1982. The Entrepreneur: An Economic Theory. Rowman & Littlefield Pub Inc. Cattell, R.B., 1966. The Scree Test for the Number of Factors, Multivariate Behavioral
Research 1 (2), 245-276. CBI - NUS, 2011. Universities must Embed Employability Skills in Course Structures -
CBI/NUS, Confederation of British Industries and National Union of Students Report, UK.
CEEC, 2012. Citizens Economic Empowerment Commission Collects K117 Billion from the K206 Billion Disbursed since its Inception in 2008; December 2012 Media Report, CEEC Report Accessed on 20 June 2013 from http://www.lusakatimes.com/2012/12/22/ceec-recovers-k117-billion-k206-billion-disbursed/.
Chamorro‐Premuzic, T., Furnham, A., 2003. Personality Traits and Academic Examination Performance, European Journal of Personality 17 (3), 237-250.
Chell, E., 2001. Entrepreneurship: Globalization, Innovation and Development. Cengage Learning.
Chell, E., 1985. The Entrepreneurial Personality: A Few Ghosts Laid to Rest? International Small Business Journal 3 (3), 43.
Chell, E., Haworth, J.M., Brearley, S.A., 1991. The Entrepreneurial Personality. Routledge London.
Chell, E., 2000. Towards Researching the''Opportunistic Entrepreneur'': A Social Constructionist Approach and Research Agenda, European Journal of Work and Organizational Psychology 9 (1), 63-80.
Chen, C.C., Greene, P.G., Crick, A., 1998. Does Entrepreneurial Self-Efficacy Distinguish Entrepreneurs from Managers? Journal of Business Venturing 13 (4), 295-316.
Chen, G., Gully, S.M., Eden, D., 2004. General Self-Efficacy and Self-Esteem: Toward Theoretical and Empirical Distinction between Correlated Self-Evaluations, Journal of Organizational Behavior 25 (3), 375-395.
Cherryholmes, C.H., 1992. Notes on Pragmatism and Scientific Realism, Educational Researcher 21 (6), 13-17.
Chigunta, F., 2002. The Socio-Economic Situation of Youth in Africa: Problems, Prospects and Options, A Paper Presented at the Youth Employment Summit, Alexandria, Egypt, 1-13.
Chigunta, F., Schnurr, J., James-Wilson, D., Torres, V., Creation, J., 2005. Being “real” about Youth Entrepreneurship in Eastern and Southern Africa, SEED Working Paper 72.
Child, J., McGrath, R.G., 2001. Organizations Unfettered: Organizational Form in an Information-Intensive Economy, Academy of Management Journal, 1135-1148.
Chimanga, K., 2007. University Graduates and Firm Creation in Preference to Professional Practice in Zambia, MBA Thesis, Copperbelt University.
Clark, B.W., Davis, C.H., Harnish, V.C., 1984. Do Courses in Entrepreneurship Aid in New Venture Creation? Journal of Small Business Management 22 (2), 26-31.
268
Clarke, K.A., 2005. The Phantom Menace: Omitted Variable Bias in Econometric Research, Conflict Management and Peace Science 22 (4), 341-352.
Clarysse, B., Wright, M., Lockett, A., Van de Velde, E., Vohora, A., 2005. Spinning Out New Ventures: A Typology of Incubation Strategies from European Research Institutions, Journal of Business Venturing 20 (2), 183-216.
Cole, A.H., 1942. Entrepreneurship as an Area of Research, The Journal of Economic History 2 (S1), 118-126.
Collins, C.J., Hanges, P.J., Locke, E.A., 2004a. The Relationship of Achievement Motivation to Entrepreneurial Behavior: A Meta-Analysis, Human Performance 17 (1), 95-117.
Collins, L., Hannon, P.D., Smith, A., 2004b. Enacting Entrepreneurial Intent: The Gaps between Student Needs and Higher Education Capability, Education Training 46 (8/9), 454-463.
Colombotos, J., 1969. Personal Versus Telephone Interviews: Effect on Responses. Public Health Reports 84 (9), 773.
Compte, A., 1975. Auguste Compte and Positivism: The Essential Writings, Ed. Gertrud Lenzer.
Compte, A., 1854. The Positive Philosophy of Auguste Compte, . Consultants, N., 2008. Survey of Entrepreneurship in Higher Education in Europe, FORA,
ECON Pöyry. Cook, M., 2010. Explaining the Determinants of Manufacturing and Non-Manufacturing
FDI Inflows in Five UK Regions, International Journal of Management Practice 4 (1), 1-26.
Cook, M., 2008. Regional and Firm Level Determinants of International Competitiveness: An Examination of SME’s Role, Capability and Competencies, PhD Thesis, University of Wolverhampton, UK.
Cope, J., 2005. Toward a Dynamic Learning Perspective of Entrepreneurship, Entrepreneurship Theory and Practice 29 (4), 373-397.
Costa Jr, P.T., McCrae, R.R., 1992. The Five-Factor Model of Personality and its Relevance to Personality Disorders, Journal of Personality Disorders 6 (4), 343-359.
Cox, L., Mueller, S., Moss, S., 2002. The Impact of Entrepreneurship Education on Entrepreneurial Self-Efficacy, International Journal of Entrepreneurship Education 1 (2), 229-245.
Cresswell, C., 1999. A Review of Enterprise Education in Universities, Welsh Enterprise Institute Report, University of Glamorgan, Pontypridd.
Creswell, J.W., Clark, V.L.P., 2007. Designing and Conducting Mixed Methods Research. Wiley Online Library.
Creswell, J., Plano-Clark, V., 2011. Designing and Conducting Mixed Methods Research,(Ed.) Thousand Oaks: Sage.
Creswell, J.W., 2014. Research Design: Qualitative, Quantitative, and Mixed Methods Approaches. SAGE, Los Angeles, Calif.
Creswell, J.W., 2009. Research Design: Qualitative, Quantitative, and Mixed Methods Approaches. SAGE, London.
Criscuolo, C., Gal, P., Menon, C., 2014. The Dynamics of Employment Growth: New Evidence from 17 OECD Countries and Brazil, OECD Science, Technology and Industry Policy Papers, no. 14, OECD Publishing.
Cromie, S., 2000. Assessing Entrepreneurial Inclinations: Some Approaches and Empirical Evidence, European Journal of Work and Organizational Psychology 9 (1), 7-30.
Cromie, S., 1987. Motivations of Aspiring Male and Female Entrepreneurs, Journal of Organizational Behavior 8 (3), 251-261.
Cronbach, L.J., 1951. Coefficient Alpha and the Internal Structure of Tests, Psychometrika 16 (3), 297-334.
Crotty, M., 1998. The Foundations of Social Research: Meaning and Perspective in the Research Process. Sage.
CSO, 2013. Zambian 2010 Census Data Reports, Central Statistical Office in Zambia. CSO, 2011a. Central Statistical Office, 2008 Labour Force Survey Report, Zambia.
269
CSO, 2011b. Central Statistical Office 2010/2011 Quarterly Employment and Earnings Inquiry Report, Zambia.
Culkin, N., 2013. Beyond being a Student: An Exploration of Student and Graduate Start-Ups (SGSUs) Operating from University Incubators, Journal of Small Business and Enterprise Development 20 (3), 634-649.
Cunningham, J.B., Lischeron, J., 1991. Defining Entrepreneurship, Journal of Small Business Management 29 (1), 45-61.
Curran, J., Burrows, R., 1987. Ethnographic Approaches to the Study of the Small Business Owner, Small Business Development: Some Current Issues, Aldershot: Avebury , 3-24.
Danermark, B., 2002. Explaining Society: Critical Realism in the Social Sciences. Psychology Press.
Davey, T., Plewa, C., Struwig, M., 2011. Entrepreneurship Perceptions and Career Intentions of International Students, Education Training 53 (5), 335-352.
Davidsson, P., 1995. Determinants of Entrepreneurial Intentions. Davidsson, P., Honig, B., 2003. The Role of Social and Human Capital among Nascent
Entrepreneurs, Journal of Business Venturing 18 (3), 301-331. Davidsson, P., 2004. Researching Entrepreneurship. Springer, New York. Davidsson, P., Wiklund, J., 1997. Values, Beliefs and Regional Variations in New Firm
Formation Rates, Journal of Economic Psychology 18 (2-3), 179-199. Davies, H., 2002. Enterprise and the Economy in Education. Davis, F.B., 1964. Educational Measurements and their Interpretation. Wadsworth
Publishing Company. De Clercq, D., Lim, D.S.K., Oh, C.H., 2011. Individual-Level Resources and New
Business Activity: The Contingent Role of Institutional Context, Entrepreneurship Theory and Practice 37 (2), 303-330.
De Faoite, D., Henry, C., Johnston, K., van der Sijde, P., 2003. Education and Training for Entrepreneurs: A Consideration of Initiatives in Ireland and the Netherlands, Education Training 45 (8/9), 430-438.
De Fruyt, F., Mervielde, I., 1996. Personality and Interests as Predictors of Educational Streaming and Achievement, European Journal of Personality 10 (5), 405-425.
De Grez, L., Van Lindt, D., 2012. The Influence of a ‘Learning-by-Doing’ Program on Entrepreneurial Perceptions of Economics Students: 20-21 September 2012; pages:156-162. In: European Conference on Innovation and Entrepreneurship Edition:7, Santarem (Portugal).
de Kok, J., de Wit, G., 2014. Do Small Businesses Create More Jobs? New Evidence for Europe, Small Business Economics, Springer 42 (2), 283-295.
De Noble, A.F., Jung, D., Ehrlich, S.B., 1999. Entrepreneurial Self-Efficacy: The Development of a Measure and its Relationship to Entrepreneurial Action, Frontiers of Entrepreneurship Research, 73-87.
De Soto, H., 2003. Mystery of Capital: Why Capitalism Triumphs in the West and Fails Everywhere Else. Basic books.
De Vries, M., 1977. The Entrepreneurial Personality: A Person at the Crossroads, Journal of Management Studies 14 (1), 34-57.
Deakins, D., Freel, M.S., Mason, K., 1996. Entrepreneurship and Small Firms. McGraw-Hill New York.
Deakins, D., Majmudar, M., Paddison, A., 1997. Developing Success Strategies for Ethnic Minorities in Business: Evidence from Scotland, Journal of Ethnic and Migration Studies 23 (3), 325-342.
Delmar, F., Davidsson, P., 2000. Where do they Come from? Prevalence and Characteristics of Nascent Entrepreneurs, Entrepreneurship & Regional Development 12 (1), 1-23.
Delmar, F., Shane, S., 2002. What Firm Founders do: A Longitudinal Study of the Start-Up Process, University of Illinois at Urbana-Champaign's Academy for Entrepreneurial Leadership Historical Research Reference in Entrepreneurship.
Denzin, N.K., 1978. The Research Act: A Theoretical Introduction to Research Methods. Denzin, N.K., 1970. The Research Act in Sociology: A Theoretical Introduction to
Sociological Methods.
270
Denzin, N.K., Lincoln, Y.S., 2011. The SAGE Handbook of Qualitative Research. Sage. Denzin, N.K., Lincoln, Y.S., Smith, L.T., 2008. Handbook of Critical and Indigenous
Methodologies. Sage. DeTienne, D.R., Chandler, G.N., 2004. Opportunity Identification and its Role in the
Entrepreneurial Classroom: A Pedagogical Approach and Empirical Test, Academy of Management Learning & Education 3 (3), 242-257.
DeVellis, R.F., 2003. Scale Development: Theory and Applications Second Edition (Applied Social Research Methods).
Dewey, J., 1931. George Herbert Mead, The Journal of Philosophy 28 (12), 309-314. Dictionary, O.E., 2011. Oxford University Press. 2011. Dillman, D.A., 2000. Mail and Internet Surveys: The Tailored Design Method. Wiley New
York. DiMaggio, P.J., Powell, W.W., 1983. The Iron Cage Revisited: Institutional Isomorphism
and Collective Rationality in Organizational Fields, American Sociological Review , 147-160.
do Paço, A., Ferreira, J.M., Raposo, M., Rodrigues, R.G., Dinis, A., 2013. Entrepreneurial Intentions: Is Education enough? International Entrepreneurship and Management Journal, 1-19.
Dohse, D., Walter, S., 2012. Knowledge Context and Entrepreneurial Intentions among Students, Small Business Economics 39 (4), 877-895.
Douglas, E.J., Shepherd, D.A., 2002. Self-Employment as a Career Choice: Attitudes, Entrepreneurial Intentions, and Utility Maximization, Entrepreneurship Theory and Practice 26 (3), 81-90.
Draycott, M., Rae, D., 2011. Enterprise Education in Schools and the Role of Competency Frameworks, International Journal of Entrepreneurial Behaviour & Research 17 (2), 127-145.
Drucker, P.F., 1985. Entrepreneurial Strategies, California Management Review 27 (2), 9-25.
Dyer, J.,W.Gibb, 1994. Toward a Theory of Entrepreneurial Careers, Entrepreneurship: Theory & Practice 19 (2), 7-21.
Ebner, A., 2006. Institutions, Entrepreneurship, and the Rationale of Government: An Outline of the Schumpeterian Theory of the State, Journal of Economic Behavior & Organization 59 (4), 497-515.
Edelman, L.F., Manolova, T.S., Brush, C.G., 2008. Entrepreneurship Education: Correspondence between Practices of Nascent Entrepreneurs and Textbook Prescriptions for Success, Academy of Management Learning & Education 7 (1), 56-70.
Edwards, L.J., Muir, E.J., 2005. Promoting Entrepreneurship at the University of Glamorgan through Formal and Informal Learning, Journal of Small Business and Enterprise Development 12 (4), 613-626.
Engle, R., Schlaegel, C., Dimitriadi, N., 2011. Institutions and Entrepreneurial Intent:A Cross-Country Study, Journal of Developmental Entrepreneurship 16 (2), 227-250.
Eriksson, K., Lindström, U.Å, 1997. Abduction—a Way to Deeper Understanding of the World of Caring, Scandinavian Journal of Caring Sciences 11 (4), 195-198.
Ertuna, Z.I., Gurel, E., 2011. The Moderating Role of Higher Education on Entrepreneurship, Education Training 53 (5), 387-402.
Fairlie, R.W., Holleran, W., 2011. Entrepreneurship Training, Risk Aversion and Other Personality Traits: Evidence from a Random Experiment, Journal of Economic Psychology .
Fairlie, R.W., Robb, A., 2006. Families, Human Capital, and Small Business: Evidence from the Characteristics of Business Owners Survey, Indus.& Lab.Rel.Rev. 60, 225.
Falck, O., Heblich, S., Luedemann, E., 2012. Identity and Entrepreneurship: Do School Peers Shape Entrepreneurial Intentions? Small Business Economics 39 (1), 39-59.
Fallon, G., Cook, M., Billimoria, A., 2001. What Factors Attract Foreign Direct Investment? Teaching Business and Economics 5, 13-18
Farashah, A.D., 2013. The Process of Impact of Entrepreneurship Education and Training on Entrepreneurship Perception and Intention: Study of Educational System of Iran, Education Training 55 (8/9), 9-9.
271
Faulconer, J.E., Williams, R.N., 1985. Temporality in Human Action: An Alternative to Positivism and Historicism. American Psychologist 40 (11), 1179.
Fayolle, A., 2007. Handbook of Research in Entrepreneurship Education: A General Perspective. Edward Elgar Pub.
Fayolle, A., Gailly, B., 2009. Assessing the Impact of Entrepreneurship Education: A Methodology and Three Experiments from French Engineering Schools, Handbook of University-Wide Entrepreneurship Education, 203.
Fayolle, A., Gailly, B., 2004. Using the Theory of Planned Behaviour to Assess Entrepreneurship Teaching Programs: A First Experimentation. In: IntEnt2004 Conference.
Fayolle, A., Gailly, B., Lassas-Clerc, N., 2006a. Assessing the Impact of Entrepreneurship Education Programmes: A New Methodology, Journal of European Industrial Training 30 (9), 701-720.
Fayolle, A., Gailly, B., Lassas-Clerc, N., 2006b. Effect and Counter-Effect of Entrepreneurship Education and Social Context on Student's Intentions, Estudios De Economía Aplicada 24 (2), 509-524.
Fayolle, A., Liñán, F., 2014. The Future of Research on Entrepreneurial Intentions, Journal of Business Research 67 (5), 663-666.
Fielding, J., Fielding, N., 2008. Synergy and Synthesis: Integrating Qualitative and Quantitative Data.
Fielding, N., 2010. Mixed Methods Research in the Real World, International Journal of Social Research Methodology 13 (2), 127-138.
Fielding, N.G., 2012. Triangulation and Mixed Methods Designs Data Integration with New Research Technologies, Journal of Mixed Methods Research 6 (2), 124-136.
Fielding, N.G., Fielding, J.L., 1986. Linking Data: The Articulation of Qualitative and Quantitative Methods in Social Research, Beverly Hills (CA): Sage , 41-53.
Fiet, J.O., 2001. The Pedagogical Side of Entrepreneurship Theory, Journal of Business Venturing 16 (2), 101-117.
Fishbein, M., Ajzen, I., 1975. Belief, Attitude, Intention and Behaviour: An Introduction to Theory and Research. Addison-Wesley.
Fishbein, M., Ajzen, I., 2011. Predicting and Changing Behavior: The Reasoned Action Approach. Taylor & Francis.
Fitzsimmons, J.R., Douglas, E.J., 2011. Interaction between Feasibility and Desirability in the Formation of Entrepreneurial Intentions, Journal of Business Venturing 26 (4), 431-440.
Forbes, D.P., 1999. Cognitive Approaches to New Venture Creation, International Journal of Management Reviews 1 (4), 415.
Fraboni, M., Saltstone, R., 1990. First and Second Generation Entrepreneur Typologies: Dimensions of Personality. Journal of Social Behavior & Personality.
Frank, H., Lueger, M., Korunka, C., 2007. The Significance of Personality in Business Start-Up Intentions, Start-Up Realization and Business Success, Entrepreneurship & Regional Development 19 (3), 227-251.
Frederking, L.C., 2004. A Cross-National Study of Culture, Organization and Entrepreneurship in Three Neighbourhoods, Entrepreneurship & Regional Development 16 (3), 197-215.
Fretschner, M., Weber, S., 2013. Measuring and Understanding the Effects of Entrepreneurial Awareness Education, Journal of Small Business Management 51 (3), 410-428.
Fritz, M.S., MacKinnon, D.P., 2007. Required Sample Size to Detect the Mediated Effect, Psychological Science (Wiley-Blackwell) 18 (3), 233-239.
Galloway, L., Anderson, M., Brown, W., Wilson, L., 2005. Enterprise Skills for the Economy, Education Training 47 (1), 7-17.
Gartner, W., Thomas, R., 1989. Factors which Influence a New Firm’s Ability to Accurate Forecast New Product Sales, Frontiers of Entrepreneurship Research, S , 408-421.
Gartner, W.B., 1990. What are we Talking about when we Talk about Entrepreneurship? Journal of Business Venturing 5 (1), 15-28.
Gartner, W.B., 1989a. Some Suggestions for Research on Entrepreneurial Traits and Characteristics, Entrepreneurship Theory and Practice 14 (1), 27-37.
272
Gartner, W.B., Mitchell, T.R., Vesper, K.H., 1989. A Taxonomy of New Business Ventures, Journal of Business Venturing 4 (3), 169-186.
Gartner, W.B., Thomas, R.J., 1993. Factors Affecting New Product Forecasting Accuracy in New Firms, Journal of Product Innovation Management 10 (1), 35-52.
Gartner, W., 2010. A New Path to the Waterfall: A Narrative on a use of Entrepreneurial Narrative, International Small Business Journal 28 (1), 6-19.
Gartner, W.B., 1989b. 'Who is an Entrepreneur?' is the Wrong Question, Entrepreneurship Theory and Practice 13 (4), 47.
Gartner, W.B., 1985. A Conceptual Framework for Describing the Phenomenon of New Venture Creation, Academy of Management Review 10 (4), 696-706.
Gaspar, F.C., 2009. The Stimulation of Entrepreneurship through Venture Capital and Business Incubation, International Journal of Entrepreneurship and Innovation Management 9 (4), 396-415.
Gasse, Y., Tremblay, M., 2011. Entrepreneurial Beliefs and Intentions: A Cross-Cultural Study of University Students in Seven Countries, International Journal of Business 16 (4), 303.
Gatewood, E.J., Shaver, K.G., Gartner, W.B., 1995. A Longitudinal Study of Cognitive Factors Influencing Start-Up Behaviors and Success at Venture Creation, Journal of Business Venturing 10 (5), 371-391.
Gedeon, S., 2010. What is Entrepreneurship? Entrepreneurial Practice Review 1 (3). Gendron, G., Case, S., Goldman, M., Golisano, T., Laybourne, G., Taylor, J., Webber, A.,
2004. Practitioners' Perspectives on Entrepreneurship Education: An Interview with Steve Case, Matt Goldman, Tom Golisano, Geraldine Laybourne, Jeff Taylor, and Alan Webber, Academy of Management Learning & Education , 302-314.
Gergen, K.J., 1985. The Social Constructionist Movement in Modern Psychology. American Psychologist 40 (3), 266.
Giacomin, O., Janssen, F., Pruett, M., Shinnar, R.S., Llopis, F., Toney, B., 2011. Entrepreneurial Intentions, Motivations and Barriers: Differences among American, Asian and European Students, International Entrepreneurship and Management Journal 7 (2), 219-238.
Gibb, A., 2007. Creating the Entrepreneurial University: Do we Need a Wholly Different Model of Entrepreneurship, Handbook of Research in Entrepreneurship Education, A General Perspective 1, 67-103.
Gibb, A., Cotton, J., 1998a. Work Futures and the Role of Entrepreneurship and Enterprise in Schools and further Education. In: Background Keynote Paper to the Creating the Leading Edge Conference.
Gibb, A., Hannon, P., 2005. Towards the Entrepreneurial University, Policy Paper 3. Gibb, A., Ritchie, J., 1982. Understanding the Process of Starting Small Businesses,
International Small Business Journal 1 (1), 26-45. Gibb, A.A., 2000. SME Policy, Academic Research and the Growth of Ignorance, Mythical
Concepts, Myths, Assumptions, Rituals and Confusions, International Small Business Journal 18 (3), 13.
Gibb, A., Cotton, J., 1998b. Entrepreneurship in Schools and College Education–creating the Leading Edge. In: Background Paper Presented at the Conference on Work Futures and the Role of Entrepreneurship and Enterprise in Schools and further Education.
Gibb, A., 2002. Creating Conducive Environments for Learning and Entrepreneurship: Living with, Dealing with, Creating and Enjoying Uncertainty and Complexity, Industry and Higher Education 16 (3), 135-148.
Gibcus, P., de Kok, J., Snijders, J., Smit, L., van der Linden, B., 2012. Effects and Impact of Entrepreneurship Programmes in European Higher Education.
Gilad, B., Levine, P., 1986. A Behavioral Model of Entrepreneurial Supply, Journal of Small Business Management 24 (4), 45-53.
Gilbert, A., 2002. On the Mystery of Capital and the Myths of Hernando De Soto: What Difference does Legal Title make? International Development Planning Review 24 (1), 1-19.
Gill, J., Johnson, P., 2002. Research Methods for Managers. Sage, London.
273
Glaser, B.G., Strauss, A.L., 2009. The Discovery of Grounded Theory: Strategies for Qualitative Research. Transaction Books.
Gnyawali, D.R., Fogel, D.S., 1994. Environments for Entrepreneurship Development: Key Dimensions and Research Implications, Entrepreneurship: Theory & Practice 18 (4), 43-62.
Gollwitzer, P.M., 1996. The Volitional Benefits of Planning, The Psychology of Action: Linking Cognition and Motivation to Behavior 13, 287-312.
Gomez-Mejia, L., Balkin, D.B., 1989. Effectiveness of Individual and Aggregate Compensation Strategies, Industrial Relations 28 (3).
Gray, C., 2006. Absorptive Capacity, Knowledge Management and Innovation in Entrepreneurial Small Firms, International Journal of Entrepreneurial Behaviour & Research 12 (6), 345-360.
Green, W.S., 2009. From Commerce to Culture: Entrepreneurship in the Mainstream, Handbook of University-Wide Entrepreneurship Education, Edward Elgar, Northampton, MA, 15-20.
Greenfield, S.M., Strickon, A., 1986. Entrepreneurship and Social Change, University Press of America (2), 4-18.
Greenfield, S.M., Strickon, A., 1981. A New Paradigm for the Study of Entrepreneurship and Social Change, Economic Development and Cultural Change 29 (3), 467-499.
Greenwald, A.G., Banaji, M.R., 1995. Implicit Social Cognition: Attitudes, Self-Esteem, and Stereotypes. Psychological Review 102 (1), 4.
Guba, E.G., 1990. The Paradigm Dialog. Sage. Guba, E.G., Lincoln, Y.S., 1994. Competing Paradigms in Qualitative Research,
Handbook of Qualitative Research 2, 163-194. Guerrero, M., Rialp, J., Urbano, D., 2008. The Impact of Desirability and Feasibility on
Entrepreneurial Intentions: A Structural Equation Model, International Entrepreneurship and Management Journal 4 (1), 35-50.
Gurel, E., Altinay, L., Daniele, R., 2010. Tourism Students’ Entrepreneurial Intentions, Annals of Tourism Research 37 (3), 646-669.
Guzman-Cuevas, J., 1994. Towards a Taxonomy of Entrepreneurial Theories, International Small Business Journal 12, 77+.
Haase, H., Lautenschlager, A., Rena, R., 2011. The Entrepreneurial Mind-Set of University Students: A Cross-Cultural Comparison between Namibia and Germany, International Journal of Education Economics and Development 2 (2), 113-129.
Hair, J., Black, W., Babin, B., Anderson, R., Tatham, R., 2006. Multivariate Data Analysis Sixth Edition Pearson Education, New Jersey.
Hannon, P.D., 2005. Philosophies of Enterprise and Entrepreneurship Education and Challenges for Higher Education in the UK, The International Journal of Entrepreneurship and Innovation 6 (2), 105-114.
Hansemark, O.C., 1998. The Effects of an Entrepreneurship Programme on Need for Achievement and Locus of Control of Reinforcement, International Journal of Entrepreneurial Behaviour & Research 4 (1), 28-50.
Hansemark, O.C., 2003. Need for Achievement, Locus of Control and the Prediction of Business Start-Ups: A Longitudinal Study, Journal of Economic Psychology 24 (3), 301-319.
Harrison, R.T., Leitch, C., 2010. Voodoo Institution Or Entrepreneurial University? Spin-Off Companies, the Entrepreneurial System and Regional Development in the UK, Regional Studies 44 (9), 1241-1262.
Hawley, F.B., 1907. Enterprise and the Productive Process... Putnam. Hayek, F.A., 1945. The use of Knowledge in Society, The American Economic Review 35
(4), 519-530. Hayes, A.F., 2013. Introduction to Mediation, Moderation, and Conditional Process
Analysis: A Regression-Based Approach. Guilford Press. Hayes, A.F., 2009. Beyond Baron and Kenny: Statistical Mediation Analysis in the New
Millennium, Communication Monographs 76 (4), 408-420. Hébert, R.F., 1981. Richard Cantillon's Early Contributions to Spatial Economics,
Economica 48 (189), 71-77.
274
Hempel, C.G., Oppenheim, P., 1948. Studies in the Logic of Explanation, Philosophy of Science 15 (2), 135-175.
Henley, A., 2007. Entrepreneurial Aspiration and Transition into Self-Employment: Evidence from British Longitudinal Data, Entrepreneurship & Regional Development 19 (3), 253-280.
Henry, C., Hill, F., Leitch, C., 2005a. Entrepreneurship Education and Training: Can Entrepreneurship be Taught? Part I, Education Training 47 (2), 98-111.
Henry, C., Hill, F., Leitch, C., 2005b. Entrepreneurship Education and Training: Can Entrepreneurship be Taught? Part II, Education Training 47 (3), 158-169.
Henry, C., Hill, F., Leitch, C., 2003. Entrepreneurship Education and Training. Ashgate Pub Ltd.
Henry, C., 2013. Entrepreneurship Education in HE: Are Policy Makers Expecting Too Much? Education Training 55 (8/9), 7-7.
Henry, C., Hill, F.M., Leitch, C.M., 2004. The Effectiveness of Training for New Business Creation: A Longitudinal Study, International Small Business Journal 22, 249+.
Hermann, B., 2011. Personality Aspects of Entrepreneurship: A Look at Five Meta-Analyses, Personality and Individual Differences 51 (3), 222-230.
Heron, J., 1996. Co-Operative Inquiry: Research into the Human Condition. Sage. Herrero, E., Van Dorp, K., 2012. Methodology and Evaluation of Entrepreneurship
Courses, International Journal of Business Research and Management (IJBRM) 1 (3), 132-155.
Herrington, M., Kelley, D., 2012. African EntrepreneurReport, Global Entrepreneurship Monitor, 2012.
Heriot, K.C., Campbell, N.D., Finney, R.Z., 2004. Omitted Variable Bias in the Link between Planning and Performance, New England Journal of Entrepreneurship 7(2), 6.
Herrmann, K., Hannon, P., Cox, J., Ternouth, P., Crowley, T., 2008. Developing Entrepreneurial Graduates: Putting Entrepreneurship at the Centre of Higher Education, Council for Industry and Higher Education (CIHE), National Council for Graduate Entrepreneurship (NCGE) and National Endowment for Science, Technology and the Arts (NESTA), London.
Hessels, J., van Stel, A., 2011. Entrepreneurship, Export Orientation, and Economic Growth, Small Business Economics 37 (2), 255-268.
Highfield, R., Smiley, R., 1987. New Business Starts and Economic Activity: An Empirical Investigation, International Journal of Industrial Organization 5 (1), 51-66.
Hills, G.E., 1988. Variations in University Entrepreneurship Education: An Empirical Study of an Evolving Field, Journal of Business Venturing 3 (2), 109-122.
Hindle, K., 2007. Teaching Entrepreneurship at University: From the Wrong Building to the Right Philosophy, Handbook of Research in Entrepreneurship Education 1, 104-126.
Hindle, K., 2002. A Grounded Theory for Teaching Entrepreneurship using Simulation Games, Simulation & Gaming 33 (2), 236-241.
Hindle, K., Al-Shanfari, D., 2011. 2 Mapping the Landscape of New Venture Creation Research, Handbook of Research on New Venture Creation, 14.
Hindle, K., Klyver, K., Jennings, D.F., 2009. An “Informed” Intent Model: Incorporating Human Capital, Social Capital, and Gender Variables into the Theoretical Model of Entrepreneurial Intentions, Understanding the Entrepreneurial Mind, 35-50.
Hisrich, R.D., Brush, C.G., 1985. Women and Minority Entrepreneurs: A Comparative Analysis, Frontiers of Entrepreneurship Research, 566-587.
Hisrich, R.D., Peters, M.P., Shepherd, D., 2005. Entrepreneurship, 2005. McGraw-Hill. Hisrich, R., Peters, M., 1995. Entrepreneurship–Starting, Developing and Managing a
New Enterprise, Richard D., Inwin, INC, USA. Hitt, M.A., Beamish, P.W., Jackson, S.E., Mathieu, J.E., 2007. Building Theoretical and
Empirical Bridges Across Levels: Multilevel Research in Management, Academy of Management Journal 50 (6), 1385-1399.
Ho, Y., Wong, P., 2007. Financing, Regulatory Costs and Entrepreneurial Propensity, Small Business Economics 28 (2-3), 187-204.
Hock-Beng, C., 1990. Schumpeterian and Austrian Entrepreneurship: Unity within Duality, Journal of Business Venturing 5 (6), 341-347.
275
Hofstede, G.H., 1984. Culture's Consequences: International Differences in Work-Related Values. Sage Publications, Inc.
Hofstede, G.H., 2014. What about Zambia? http://geert-hofstede.com/zambia.html accessed 25 September 2014 10:15 AM UK
Holmes, T.J., Schmitz Jr, J.A., 1990. A Theory of Entrepreneurship and its Application to the Study of Business Transfers, Journal of Political Economy 98 (2), 265.
Honig, B., 2004. Entrepreneurship Education: Toward a Model of Contingency-Based Business Planning, Academy of Management Learning & Education 3 (3), 258-273.
Hoskisson, R.E., Covin, J., Volberda, H.W., Johnson, R.A., 2011. Revitalizing Entrepreneurship: The Search for New Research Opportunities, Journal of Management Studies.
House, R.J., Shane, S.A., Herold, D.M., 1996. Rumors of the Death of Dispositional Research are Vastly Exaggerated, Academy of Management Review 21 (1), 203-224.
Howell, J.M., Shea, C.M., Higgins, C.A., 2005. Champions of Product Innovations: Defining, Developing, and Validating a Measure of Champion Behavior, Journal of Business Venturing 20 (5), 641-661.
Hytti, U., O’Gorman, C., 2004. What is “enterprise Education”? an Analysis of the Objectives and Methods of Enterprise Education Programmes in Four European Countries, Education Training 46 (1), 11-23.
Iakovleva, T., Kolvereid, L., Stephan, U., 2011. Entrepreneurial Intentions in Developing and Developed Countries, Education Training 53 (5), 353-370.
ICMM, 2014. Enhancing Mining’s Contribution to the Zambian Economy and Society, International Council for Mining and Metals Report.
ILO, 1993. International Labour Organisation (ILO) Resolution Concerning the International Classification of Status in Employment (ICSE), Standards and Guidelines:Resolutions Adopted by International Conferences of Labour Statisticians.
Jack, S.L., Anderson, A.R., 1999. Entrepreneurship Education within the Enterprise Culture: Producing Reflective Practitioners, International Journal of Entrepreneurial Behaviour & Research 5 (3), 110-125.
Jack, S.L., Anderson, A.R., 1998. Entrepreneurship Education within the Condition of Entreprenology. In: Proceedings of the Conference on Enterprise and Learning.
James, L.R., Brett, J.M., 1984. Mediators, Moderators, and Tests for Mediation. Journal of Applied Psychology 69 (2), 307.
Jamieson, I., 1984. Schools and Enterprise, Education for Enterprise 1 (1), 7-18. Jenks, L.H., 1950. Approaches to Entrepreneurial Personality, Explorations in
Entrepreneurial 2, 91-99. Jick, T.D., 1979. Mixing Qualitative and Quantitative Methods: Triangulation in Action,
Administrative Science Quarterly 24 (4), 602-611. Johannisson, B., 1991. University Training for Entrepreneurship: Swedish Approaches,
Entrepreneurship & Regional Development 3 (1), 67-82. Johannisson, B., Landstrom, H., Rosenberg, J., 1998. University Training for
Entrepreneurship—an Action Frame of Reference, European Journal of Engineering Education 23 (4), 477-496.
Johnson, G., Whittington, R., Scholes, K., Pyle, S., 2011. Exploring Strategy: Text & Cases. Financial Times Prentice Hall Harlow.
Johnston, R.B., Smith, S.P., 2010. 2. How Critical Realism Clarifies Validity Issues in Theory-Testing Research: Analysis and Case, Dennis N.Hart, Shirley D.Gregor Edition, Information Systems Foundations: The Role of Design Science, 21-47.
Jose, P.E., 2013. Doing Statistical Mediation and Moderation. Guilford Press. Judd, C.M., Kenny, D.A., 2010. Data Analysis in Social Psychology: Recent and Recurring
Issues. Wiley Online Library. Judd, C.M., Kenny, D.A., 1981a. Estimating the Effects of Social Interventions.CUP
Archive. Judd, C.M., Kenny, D.A., 1981b. Process Analysis Estimating Mediation in Treatment
Evaluations, Evaluation Review 5 (5), 602-619. Judge, T.A., Erez, A., Bono, J.E., Thoresen, C.J., 2002. Are Measures of Self-Esteem,
Neuroticism, Locus of Control, and Generalized Self-Efficacy Indicators of a Common Core Construct? Journal of Personality and Social Psychology 83 (3), 693.
276
Kaiser, H.F., 1970. A Second Generation Little Jiffy, Psychometrika 35 (4), 401-415. Kaiser, H.F., Rice, J., 1974. Little Jiffy, Mark IV. Educational and Psychological
Measurement. Katz, J., 1992. A Psychosocial Cognitive Model of Employment Status Choice,
Entrepreneurship: Theory and Practice 17. Katz, J., Gartner, W.B., 1988. Properties of Emerging Organizations, Academy of
Management Review 13 (3), 429-441. Kautonen, T., van Gelderen, M., Fink, M., 2013. Robustness of the Theory of Planned
Behavior in Predicting Entrepreneurial Intentions and Actions, Entrepreneurship Theory and Practice, n/a-n/a.
Keeble, D., Bryson, J., Wood, P., 1992. The Rise and Role of Small Service Firms in the United Kingdom, International Small Business Journal 11 (1), 11-22.
Kelley, D., Bosma, N., Amorós, J.E., 2011. Global Entrepreneurship Monitor 2010 Global Report, Babson College and Universidad Del Desarrollo.
Kelley, D.J., Singer, S., Herrington, M.D., 2012. The Global Entrepreneurship Monitor, . Kenny, D.A., 2008. Reflections on Mediation, Organizational Research Methods 11 (2),
353-358. Keynes, J.M., 1936. The General Theory of Employment Interest and Money. the
Collected Writings of John Maynard Keynes Vol. VII. Kilby, P., 1971. Entrepreneurship and Economic Development. Free Press New York. Kirby, D.A., 2004. Entrepreneurship Education: Can Business Schools Meet the
Challenge? Education Training 46 (8/9), 510-519. Kirchhoff, B.A., 1994. Entrepreneurship and Dynamic Capitalism: The Economics of
Business Firm Formation and Growth. Praeger Publishers. Kirzner, I., 1973. Competition and Entrepreneurship. Kirzner, I.M., 1997. Entrepreneurial Discovery and the Competitive Market Process: An
Austrian Approach, Journal of Economic Literature 35 (1), 60-85. Kirzner, I.M., 1978. Competition and Entrepreneurship. University of Chicago Press. Klein, P.G., Bullock, J.B., 2006. Can Entrepreneurship be Taught? Journal of Agricultural
and Applied Economics 38 (2), 429. Klein, P.G., Cook, M.L., 2006. TW Schultz and the Human-Capital Approach to
Entrepreneurship, Applied Economic Perspectives and Policy 28 (3), 344-350. Knight, F.H., 1921. Risk, Uncertainty and Profit, Reprint of Scarce Texts in Economic and
Political Science 16. Kolb, D.A., Boyatzis, R.E., Mainemelis, C., 2001. Experiential Learning Theory: Previous
Research and New Directions, Perspectives on Thinking, Learning, and Cognitive Styles 1, 227-247.
Kolb, A.Y., Kolb, D.A., 2005. Learning Styles and Learning Spaces: Enhancing Experiential Learning in Higher Education, Academy of Management Learning & Education , 193-212.
Kolb, D.A., 1984. Experiential Learning: Experience as the Source of Learning and Development. Prentice-Hall Englewood Cliffs, NJ.
Kolvereid, L., 1996a. Prediction of Employment Status Choice Intentions, Journal Article by Lars Kolvereid; Entrepreneurship: Theory and Practice 21.
Kolvereid, L., 1996b. Organizational Employment Versus Self-Employment: Reasons for Career Choice Intentions, Entrepreneurship: Theory & Practice 20 (3), 23-31.
Kostova, T., 1997. Country Institutional Profiles: Concept and Measurement, Academy of Management Best Papers Proceedings, 180-184.
Kotler, P., 2011. Reinventing Marketing to Manage the Environmental Imperative, Journal of Marketing 75 (4), 132-135.
Kotler, P., Armstrong, G., 2013. Principles of Marketing 15th Global Edition. Pearson Krathwohl, D.R., Bloom, B.S., 2002. Taxonomy of Educational Objectives: The
Classification of Educational Goals. Longman. Kristiansen, S., Indarti, N., 2004. Entrepreneurial Intention among Indonesian and
Norwegian Students, Journal of Enterprising Culture 12 (1), 55-78. Krueger Jr, N.F., 2009. The Microfoundations of Entrepreneurial Learning and Education:
The Experiential Essence of Entrepreneurial Cognition, Handbook of University-Wide Entrepreneurship Education, 35-59.
277
Krueger Jr, N.F., 2007a. The Cognitive Infrastructure of Opportunity Emergence, Entrepreneurship: Concepts, Theory and Perspective, Springer, Berlin, 185-206.
Krueger Jr, N.F., 2007b. What Lies Beneath? The Experiential Essence of Entrepreneurial Thinking, Entrepreneurship Theory and Practice 31 (1), 123-138.
Krueger JR, N.F., Reilly, M.D., Carsrud, A.L., 2000. Competing Models of Entrepreneurial Intentions, Journal of Business Venturing 15 (5-6), 411-432.
Krueger, J.N.F., Carsrud, A.L., 1993. Entrepreneurial Intentions: Applying the Theory of Planned Behaviour, Entrepreneurship & Regional Development 5 (4), 315-330.
Krueger, N., 2009. Entrepreneurial Intentions are Dead: Long Live Entrepreneurial Intentions, Understanding the Entrepreneurial Mind, 51-72.
Krueger, N., 1993. The Impact of Prior Entrepreneurial Exposure on Perceptions of New Venture Feasibility and Desirability, Entrepreneurship: Theory and Practice 18 (1).
Krueger, N.F., Brazeal, D.V., 1994. Entrepreneurial Potential and Potential Entrepreneurs, Entrepreneurship Theory and Practice 18, 91-91.
Krueger, N., 2008. Entrepreneurial Resilience: Real & Perceived Barriers to Implementing Entrepreneurial Intentions, Social Science Research Network.
Krueger, N., Dickson, P.R., 1994. How Believing in Ourselves Increases Risk Taking:
Perceived Self‐Efficacy and Opportunity Recognition, Decision Sciences 25 (3), 385-400.
Kuhn, T.S., 1970. The Structure of Scientific Revolutions, Chicago/London. Kuratko, D.F., 2003. Entrepreneurship Education: Emerging Trends and Challenges for
the 21st Century. In: A Paper Presented at a Meeting of the US Association of Small Business & Entrepreneurship.
Kuratko, D.F., 2005. The Emergence of Entrepreneurship Education: Development, Trends, and Challenges, Entrepreneurship Theory and Practice 29 (5), 577-598.
Küttim, M., Kallaste, M., Venesaar, U., Kiis, A., 2014. Entrepreneurship Education at University Level and Students’ Entrepreneurial Intentions, Procedia-Social and Behavioral Sciences 110, 658-668.
Laing, R.D., 1967. The Politics of Experience & the Bird of Paradise Harmondsworth, UK: Pen .
Lalkaka, R., 2009. National Innovation Systems: The Role of Academia, Enterprise, and State,^ In, Asia Pacific Journal of Entrepreneurship 3 (2), 5-28.
Lau, C.M., Woodman, R.W., 1995. Understanding Organizational Change: A Schematic Perspective, Academy of Management Journal, 537-554.
Lawson, T., 1996. Developments in Economics as Realist Social Theory, Review of Social Economy 54 (4), 405-422.
Layder, D., Layder, 1993. New Strategies in Social Research: An Introduction and Guide. Polity Press Cambridge.
Learned, K.E., 1992. What Happened before the Organization? A Model of Organization Formation, Entrepreneurship Theory and Practice 17 (1).
LeCompte, M.D., Goetz, J.P., 1982. Problems of Reliability and Validity in Ethnographic Research, Review of Educational Research 52 (1), 31-60.
Lee, D.Y., Tsang, E.W.K., 2001. The Effects of Entrepreneurial Personality, Background and Network Activities on Venture Growth*, Journal of Management Studies 38 (4), 583-602.
Lee, S.H., Wong, P.K., 2004. An Exploratory Study of Technopreneurial Intentions: A Career Anchor Perspective, Journal of Business Venturing 19 (1), 7-28.
Leibenstein, H., 1966. Allocative Efficiency Vs." X-Efficiency", The American Economic Review 56 (3), 392-415.
Leightner, J.E., Inoue, T., 2012. Solving the Omitted Variables Problem of Regression Analysis using the Relative Vertical Position of Observations, Advances in Decision Sciences 2012.
Levenburg, N.M., Lane, P.M., Schwarz, T.V., 2006. Interdisciplinary Dimensions in Entrepreneurship, Journal of Education for Business 81 (5), 275-281.
Levie, J., 1999. Entrepreneurship Education in Higher Education in England: A Survey, London Business School, London.
Lewin, K., Cartwright, D., 1952. Field Theory in Social Science: Selected Theoretical Papers. Tavistock London.
278
Lewis, S.E., Shaw, J.L., Heitz, J.O., Webster, G.H., 2009. Attitude Counts: Self-Concept and Success in General Chemistry, Journal of Chemical Education 86 (6), 744.
Lewis, W.A., 1954. Economic Development with Unlimited Supplies of Labour, The Manchester School 22 (2), 139-191.
Li, J., Zhang, Y., Matlay, H., 2003. Entrepreneurship Education in China, Education Training 45 (8/9), 495-505.
Li, W., 2007. Ethnic Entrepreneurship: Studying Chinese and Indian Students in the United States, Journal of Developmental Entrepreneurship 12 (04), 449-466.
Lievens, F., Coetsier, P., De Fruyt, F., De Maeseneer, J., 2002. Medical Students' Personality Characteristics and Academic Performance: A Five‐factor Model Perspective, Medical Education 36 (11), 1050-1056.
Lim, D.S.K., Morse, E.A., Mitchell, R.K., Seawright, K.K., 2010. Institutional Environment and Entrepreneurial Cognitions: A Comparative Business Systems Perspective, Entrepreneurship: Theory & Practice 34 (3), 491-516.
Liñán, F., 2008. Skill and Value Perceptions: How do they Affect Entrepreneurial Intentions? International Entrepreneurship and Management Journal 4 (3), 257-272.
Liñán, F., Chen, Y.W., 2009. Development and Cross‐Cultural Application of a Specific Instrument to Measure Entrepreneurial Intentions, Entrepreneurship Theory and Practice 33 (3), 593-617.
Liñán, F., Urbano, D., Guerrero, M., 2011a. Regional Variations in Entrepreneurial Cognitions: Start-Up Intentions of University Students in Spain, Entrepreneurship and Regional Development 23 (3-4), 187-215.
Liñán, F., Rodríguez-Cohard, J.C., Rueda-Cantuche, J.M., 2011b. Factors Affecting Entrepreneurial Intention Levels: A Role for Education, International Entrepreneurship and Management Journal 7 (2), 195-218.
Lincoln, Y.S., Guba, E., 2000. “Paradigmatic Controversies, Contradictions, and Emerging Confluences,”, NK Denzin and Yvonna S., Lincoln (Eds.), Handbook of Qualitative Research.London: Sage, 8.
Lincoln, Y.S., Guba, E.G., 1986. But is it Rigorous? Trustworthiness and Authenticity in Naturalistic Evaluation, New Directions for Program Evaluation 1986 (30), 73-84.
Lincoln, Y.S., Guba, E.G., 1985. Establishing Trustworthiness, Naturalistic Inquiry, 289-331.
Littunen, H., 2000. Entrepreneurship and the Characteristics of the Entrepreneurial Personality, International Journal of Entrepreneurial Behaviour & Research 6 (6), 295-310.
Lord Young, 2013. Growing Your Business: A Report on Growing Micro Businesses in UK, http://smallbusinesscharter.org/images/media/mediagrowing-your-business-lord-young.pdf accessed 23.04.2014.
Lord Young, 2012. Make Business Your Business: Supporting the Start-Up and Development of Small Business in UK, http://www.ukbi.co.uk/media/download%20docs/start_up_britain_report_-_make_business_your_business_-_lord_young_-_2012.pdf accessed on 22.04.2014.
Low, M.B., MacMillan, I.C., 1988. Entrepreneurship: Past Research and Future Challenges, Journal of Management 14 (2), 139-161.
Luethje, C., Franke, N., 2004. Entrepreneurial Intentions of Business Students: A Benchmarking Study, International Journal of Innovation and Technology Management 1 (3), 269-288.
Lund, T., 2005. The Qualitative–quantitative Distinction: Some Comments, Scandinavian Journal of Educational Research 49 (2), 115-132.
Lungu, J., 2008. Socio-Economic Change and Natural Resource Exploitation: A Case Study of the Zambian Copper Mining Industry, Development Southern Africa 25 (5), 543-560.
Lungu, J., Chama, S., Mwiya, B.M.K., 2007. Quality of Employment, Implications for Policy: Evidence from Zambia.
Lüthje, C., Franke, N., 2003. The ‘making’of an Entrepreneur: Testing a Model of Entrepreneurial Intent among Engineering Students at MIT, R&D Management 33 (2), 135-147.
MacKinnon, D., 2007. Introduction to Statistical Mediation Analysis. CRC Press.
279
MacKinnon, D.P., Fairchild, A.J., 2009. Current Directions in Mediation Analysis, Current Directions in Psychological Science 18 (1), 16-20.
MacKinnon, D.P., Lockwood, C.M., Hoffman, J.M., West, S.G., Sheets, V., 2002. A Comparison of Methods to Test Mediation and Other Intervening Variable Effects. Psychological Methods 7 (1), 83.
MacKinnon, D., Coxe, S., Baraldi, A., 2012. Guidelines for the Investigation of Mediating Variables in Business Research, Journal of Business & Psychology 27 (1), 1-14.
Maimbo, S.M., Mavrotas, G., 2003. Financial Sector Reforms and Savings Mobilization in Zambia. WIDER Discussion Papers//World Institute for Development Economics (UNU-WIDER).
Mancuso, J.R., 1974. What it Takes to be an Entrepreneur: A Questionnaire Approach, Journal of Small Business Management 12 (4), 16-22.
Manolova, T.S., Eunni, R.V., Gyoshev, B.S., 2008. Institutional Environments for Entrepreneurship: Evidence from Emerging Economies in Eastern Europe, Entrepreneurship Theory and Practice 32 (1), 203-218.
Maria, M., Bygrave, W., 2001. A Dynamic Model of Entrepreneurial Learning, Entrepreneurship Theory and Practice Waco 25 (3), 5-14.
Markman, G.D., Balkin, D.B., Baron, R.A., 2002. Inventors and New Venture Formation: The Effects of General Self‐Efficacy and Regretful Thinking, Entrepreneurship Theory and Practice 27 (2), 149-165.
Marques, C.S., Ferreira, J.J., Gomes, D.N., Rodrigues, R.G., 2012. Entrepreneurship Education: How Psychological, Demographic and Behavioural Factors Predict the Entrepreneurial Intention, Education Training 54 (8/9), 657-672.
Marshall, A., 1920. Principles of Economics (London, 1920), Book VI , 618-619. Martin, B.C., McNally, J.J., Kay, M.J., 2013. Examining the Formation of Human Capital in
Entrepreneurship: A Meta-Analysis of Entrepreneurship Education Outcomes, Journal of Business Venturing 28 (2), 211-224.
Martinelli, A., 2004. The Social and Institutional Context of Entrepreneurship, Crossroads of Entrepreneurship, 53-73.
Martínez, A.C., Kelley, D., Levie, J., 2010. Global Entrepreneurship Monitor Special Report: A Global Perspective on Entrepreneurship Education and Training, Global Entrepreneurship Monitor, United States.
Matheson, D., 2008. An Introduction to the Study of Education. David Fulton Publish. Matlay, H., 2009. Entrepreneurship Education in the UK: A Critical Analysis of Stakeholder
Involvement and Expectations, Journal of Small Business and Enterprise Development 16 (2), 355-368.
Matlay, H., 2008. The Impact of Entrepreneurship Education on Entrepreneurial Outcomes, Journal of Small Business and Enterprise Development 15 (2), 382-396.
Matlay, H., 2005. Researching Entrepreneurship and Education: Part 1: What is Entrepreneurship and does it Matter? Education Training 47 (8/9), 665-677.
Matlay, H., Mitra, J., 2002. Entrepreneurship and Learning: The Double Act in the Triple Helix, The International Journal of Entrepreneurship and Innovation 3 (1), 7-16.
Matlay, H., 2010. Stakeholder Participation in, and Impact upon, entrepreneurship Education in the UK, Handbook of Research in Entrepreneurship Education: International Perspectives, Edited by Alain Fayolle 3, 110-121.
Mauer, R., Neergaard, H., Linstad, A.K., 2009. Self-Efficacy: Conditioning the Entrepreneurial Mindset, Understanding the Entrepreneurial Mind, 233-257.
Mauzu, D.M., 2000. SME Policies and Policy Formulation in SADC Countries; SMME Policy in Zambia, Friedrich-Ebert-Stiftung, Botswana http://library.fes.de/fulltext/bueros/botswana/00552013.htm.
McAuley, J., FIPD, Duberley, J., Johnson, P., 2007. Organization Theory: Challenges and Perspectives. Financial Times Prentice Hall, Harlow.
McClelland, D.C., 1967. The Achieving Society. Free Press. McClelland, D.C., 1965. N Achievement and Entrepreneurship: A Longitudinal Study.
Journal of Personality and Social Psychology 1 (4), 389. McClelland, D.C., 1961. The Achievement Society, The Achievement Society.
280
McCrae, R.R., Costa Jr, P.T., 1989. Reinterpreting the Myers‐Briggs Type Indicator from the Perspective of the Five‐Factor Model of Personality, Journal of Personality 57 (1), 17-40.
McCrae, R.R., Costa, P.T., 2004. A Contemplated Revision of the NEO Five-Factor Inventory, Personality and Individual Differences 36 (3), 587-596.
McCrae, R.R., Costa, P.T., 1985. Comparison of EPI and Psychoticism Scales with Measures of the Five-Factor Model of Personality, Personality and Individual Differences 6 (5), 587-597.
McGee, J.E., Peterson, M., Mueller, S.L., Sequeira, J.M., 2009. Entrepreneurial Self-Efficacy: Refining the Measure, Entrepreneurship Theory and Practice 33 (4), 965-988.
McGrath, R.G., MacMillan, I.C., 2000. The Entrepreneurial Mindset: Strategies for Continuously Creating Opportunity in an Age of Uncertainty. Harvard Business Press.
McMullan, C.A., Boberg, A.L., 1991. The Relative Effectiveness of Projects in Teaching Entrepreneurship, Journal of Small Business and Entrepreneurship 9 (1), 14-24.
Mcmullan, W.E., Long, W.A., 1987. Entrepreneurship Education in the Nineties, Journal of Business Venturing 2 (3), 261-275.
Mead, G.H., 2009. Mind, Self, and Society: From the Standpoint of a Social Behaviorist. University of Chicago press.
Mead, G.H., 1925. The Genesis of the Self and Social Control, International Journal of Ethics 35 (3), 251-277.
Meade, A.W., Watson, A.M., Kroustalis, C.M., 2007. Assessing Common Methods Bias in Organizational Research. In: 22nd Annual Meeting of the Society for Industrial and Organizational Psychology, New York, pp. 1-10.
Meertens, R.M., Lion, R., 2008. Measuring an Individual's Tendency to Take Risks: The Risk Propensity Scale1, Journal of Applied Social Psychology 38 (6), 1506-1520.
Meredith, G.G., Nelson, R.E., Neck, P.A., Oficina Internacional del Trabajo (Ginebra), 1982. The Practice of Entrepreneurship. International Labour Office.
Mertens, D.M., 2009. Research and Evaluation in Education and Psychology: Integrating Diversity with Quantitative, Qualitative, and Mixed Methods. Sage.
Mescon, T.S., Montanari, J., 1981. The Personalities of Independent and Franchise Entrepreneurs: An Empirical Analysis of Concepts, Journal of Enterprise Management 3 (2), 149-159.
Meyer, B.D., 1995. Natural and Quasi-Experiments in Economics, Journal of Business & Economic Statistics 13 (2), 151-161.
Meyer, J.W., Rowan, B., 1977. Institutionalized Organizations: Formal Structure as Myth and Ceremony, American Journal of Sociology 83 (2), 340-363.
Mill, J.S., 1848. The Principles of Political Economy. Wiley Online Library. Miller, D., 1983. The Correlates of Entrepreneurship in Three Types of Firms,
Management Science, 770-791. Mises, L., 1949. 1998, Human Action: A Treatise on Economics. Mitchell, R.K., Busenitz, L.W., Bird, B., Marie Gaglio, C., McMullen, J.S., Morse, E.A.,
Smith, J.B., 2007. The Central Question in Entrepreneurial Cognition Research 2007, Entrepreneurship Theory and Practice 31 (1), 1-27.
Mitra, J., 2011. UNCTAD Multi-Year Expert Meeting on Enterprise Development Policies and Capacity-Building in Science, Technology and Innovation (STI) January 16-18, 2011 Briefing Note on Pro-Poor Entrepreneurship: Issues and Policy.
Mitton, D.G., 1989. The Compleat Entrepreneur, Entrepreneurship Theory and Practice 13 (3), 9-19.
Molina-Azorín, J.F., López-Gamero, M.D., Pereira-Moliner, J., Pertusa-Ortega, E., 2012. Mixed Methods Studies in Entrepreneurship Research: Applications and Contributions, Entrepreneurship & Regional Development 24 (5), 425-456.
Morera, O.F., Castro, F.G., 2013. Important Considerations in Conducting Statistical Mediation Analyses, American Journal of Public Health 103 (3), 394-396.
Morgan, D.L., 2007. Paradigms Lost and Pragmatism Regained Methodological Implications of Combining Qualitative and Quantitative Methods, Journal of Mixed Methods Research 1 (1), 48-76.
281
Moroz, P.W., Hindle, K., 2010. Entrepreneurship as a Process: Toward Harmonizing Multiple Perspectives, Entrepreneurship Theory and Practice.
Morris, M.H., Webb, J.W., Fu, J., Singhal, S., 2013. A Competency-Based Perspective on Entrepreneurship Education: Conceptual and Empirical Insights, Journal of Small Business Management 51 (3), 352-369.
Morse, J.M., 1991. Approaches to Qualitative-Quantitative Methodological Triangulation, Nursing Research 40 (2), 120-123.
Mueller, S.L., Thomas, A.S., 2001. Culture and Entrepreneurial Potential: A Nine Country Study of Locus of Control and Innovativeness, Journal of Business Venturing 16 (1), 51-75.
Murphy, J.P., Rorty, R., 1990. Pragmatism: From Peirce to Davidson. Westview Press Boulder, CO.
Musil, C.M., Jones, S.L., Warner, C.D., 1998. Structural Equation Modeling and its Relationship to Multiple Regression and Factor Analysis, Research in Nursing & Health 21 (3), 271-281.
Mutambi, J., Byaruhanga, J.K., Trojer, L., Buhwezi, K.B., 2010. Research on the State of Business Incubation Systems in Different Countries: Lessons for Uganda, African Journal of Science, Technology, Innovation & Development 2.
Mwamba, S., Griffiths, A., Kahler, A., 2010. A Fool's Paradise? Zambia's Mining Tax Regime.
Mwiya, B., 2006. Credit Default in the Zambian Banking Sector: Need for Credit Reference Bureaus, Journal of Business 1 (2), 2-15.
Nabi, G., Holden, R., 2008. Graduate Entrepreneurship: Intentions, Education and Training, Education Training 50 (7), 545-551.
Nabi, G., Holden, R., Walmsley, A., 2010. Entrepreneurial Intentions among Students: Towards a Re-Focused Research Agenda, Journal of Small Business and Enterprise Development 17 (4), 537-551.
Nabi, G., Liñán, F., 2011. Graduate Entrepreneurship in the Developing World: Intentions, Education and Development, Education Training 53 (5), 325-334.
Nabi, G.R., Bagley, D., 1999. Graduates’ Perceptions of Transferable Personal Skills and Future Career Preparation in the UK, Education Training 41 (4), 184-193.
National Budget, 2014. National Budget for Zambia 2014. Naudé, W., Gries, T., Wood, E., Meintjies, A., 2008. Regional Determinants of
Entrepreneurial Start-Ups in a Developing Country, Entrepreneurship and Regional Development 20 (2), 111-124.
Naylor, R.W., Lamberton, C.P., West, P.M., 2012. Beyond the “like” Button: The Impact of Mere Virtual Presence on Brand Evaluations and Purchase Intentions in Social Media Settings, Journal of Marketing 76 (6), 105-120.
NBIA, 2014. US Based National Business Incubation Association, https://www.nbia.org/resource_library/what_is/index.php accessed on 22.04.2014.
Neck, H.M., Greene, P.G., 2011. Entrepreneurship Education: Known Worlds and New Frontiers, Journal of Small Business Management 49 (1), 55-70.
Neuman, W.L., 2009. Social Research Methods: Quantitative and Qualitative Methods. Neumark, D., Wall, B., Zhang, J., 2011. Do Small Businesses Create More Jobs? New
Evidence for the United States from the National Establishment Time Series, The Review of Economics and Statistics 93 (1), 16-29.
Nga, K.H.J., Shamuganathan, G., 2010. “The Influence of Personality Traits and Demographic Factors on Social Entrepreneurship Start Up Intentions.”Journal of Business Ethics 95 (2), 259-282.
Nikolova, E., Simroth, D., 2013. Does Cultural Diversity Help Or Hinder Entrepreneurs? Evidence from Eastern Europe and Central Asia, Evidence from Eastern Europe and Central Asia (May, 2013).
North, D.C., 1990. Institutions, Institutional Change, and Economic Performance. Cambridge Univ Pr.
Novick, G., 2008. Is there a Bias Against Telephone Interviews in Qualitative Research? Research in Nursing & Health 31 (4), 391-398.
Nunnally, J.C., Bernstein, I., 1978. Psychometry Theory, New York: McGraw-Hill.
282
Obschonka, M., Silbereisen, R.K., Schmitt-Rodermund, E., 2010. Entrepreneurial Intention as Developmental Outcome, Journal of Vocational Behavior 77 (1), 63-72.
Oosterbeek, H., van Praag, M., Ijsselstein, A., 2010. The Impact of Entrepreneurship Education on Entrepreneurship Skills and Motivation, European Economic Review 54 (3), 442-454.
Opdenakker, R., 2006. Advantages and Disadvantages of Four Interview Techniques in Qualitative Research. In: Forum Qualitative Sozialforschung/Forum: Qualitative Social Research.
Orhan, M., Scott, D., 2001. Why Women Enter into Entrepreneurship: An Explanatory Model, Women in Management Review 16 (5), 232-247.
Osborne, R.L., 1995. The Essence of Entrepreneurial Success, Management Decision 33 (7), 4-9.
Packham, G., Jones, P., Miller, C., Pickernell, D., Thomas, B., 2010. Attitudes Towards Entrepreneurship Education: A Comparative Analysis, Education Training 52 (8/9), 568-586.
Pallant, J., 2010. SPSS Survival Manual: A Step by Step Guide to Data Analysis using SPSS. Open University Press.
Park, H.S., Levine, T.R., 1999. The Theory of Reasoned Action and Self‐construal: Evidence from Three Cultures, Communications Monographs 66 (3), 199-218.
Patokorpi, E., 2006. Role of Abductive Reasoning in Digital Interaction. Patton, M.Q., 2005. Qualitative Research. Wiley Online Library. Patton, M.Q., 1990. Qualitative Evaluation and Research Methods. SAGE Publications. Pedler, M.M., 2012. Action Learning for Managers. Gower Publishing, Ltd. Peirce, C.S., 1955. Abduction and Induction, Philosophical Writings of Peirce 11. Penrose, E., 1959. The Growth of the Firm, White Plains, New York: ME Sharpe . Peter, J.P., 1979. Reliability: A Review of Psychometric Basics and Recent Marketing
Practices, Journal of Marketing Research, 6-17. Peterman, N.E., Kennedy, J., 2003. Enterprise Education: Influencing Students’
Perceptions of Entrepreneurship, Entrepreneurship Theory and Practice 28 (2), 129-144.
Peters, G., 2014. Africa'S Entrepreneurial Route to Growth, Business Strategy Review 25 (1), 10-14.
Peterson, R.A., 1994. A Meta-Analysis of Cronbach's Coefficient Alpha, Journal of Consumer Research 21 (2), 381-391.
Phan, P.H., Siegel, D.S., Wright, M., 2005. Science Parks and Incubators: Observations, Synthesis and Future Research, Journal of Business Venturing 20 (2), 165-182.
Pickering, J.F., 1981. A Behavioral Model of the Demand for Consumer Durables, Journal of Economic Psychology 1 (1), 59-77.
Pickernell, D., Packham, G., Jones, P., Miller, C., Thomas, B., 2011. Graduate Entrepreneurs are Different: They Access More Resources? International Journal of Entrepreneurial Behaviour & Research 17 (2), 183-202.
Pittaway, L., Cope, J., 2007. Entrepreneurship Education A Systematic Review of the Evidence, International Small Business Journal 25 (5), 479-510.
Ployhart, R.E., Moliterno, T.P., 2011. Emergence of the Human Capital Resource: A Multilevel Model, Academy of Management Review 36 (1), 127-150.
Podsakoff, P.M., MacKenzie, S.B., Lee, J., Podsakoff, N.P., 2003. Common Method Biases in Behavioral Research: A Critical Review of the Literature and Recommended Remedies. Journal of Applied Psychology 88 (5), 879.
Popper, K.R., 1959. The Logic of Scientific Discovery, London: Hutchinson 1. Popper, K.R., Popper, K.R., Popper, K.R., 1972. Objective Knowledge: An Evolutionary
Approach. Clarendon Press Oxford. Porter, M.E., 1980. Competitive Strategy: Techniques for Analyzing Industries and
Competition, New York. Potvin, P., Hasni, A., 2014. Interest, Motivation and Attitude Towards Science and
Technology at K-12 Levels: A Systematic Review of 12 Years of Educational Research, Studies in Science Education 50 (1), 85-129.
283
Prieto, L., Wang, L., Hinrichs, K.T., Aguirre-Milling, H., 2010. Propensity for Self-Employment: Contrasting the USA and Mexico, Journal of Small Business and Enterprise Development 17 (3), 315-333.
QAA, 2012. Guidance on Enterprise and Entrepreneurship to UK Higher Education Providers, Quality Assurance Authority for Higher Education in the UK.
Rae, D., 2010. Universities and Enterprise Education: Responding to the Challenges of the New Era, Journal of Small Business and Enterprise Development 17 (4), 591-606.
Rae, D., 2007a. Connecting Enterprise and Graduate Employability: Challenges to the Higher Education Culture and Curriculum? Education Training 49 (8/9), 605-619.
Rae, D., 2007b. Entrepreneurship: From Opportunity to Action. Palgrave Macmillan. Rae, D., Martin, L., Ancliff, V., Hannon, P., 2012. Enterprise and Entrepreneurship in
English Higher Education: 2010 and Beyond, Journal Small Business & Enterprise Development 19.
Rae, D., 2000. Understanding Entrepreneurial Learning: A Question of how? International Journal of Entrepreneurial Behaviour & Research 6 (3), 145-159.
Rasheed, H.S., 2000. Developing Entrepreneurial Potential in Youth: The Effects of Entrepreneurial Education and Venture Creation, Florida: University of South Florida.
Rasheed, H.S., Rasheed, B., 2003. Developing Entrepreneurial Characteristics in Youth: The Effects of Education and Enterprise Experience, Ethnic Entrepreneurship: Structure and Process.Amsterdam: Elsevier.
Ratinho, T., Henriques, E., 2010. The Role of Science Parks and Business Incubators in Converging Countries: Evidence from Portugal, Technovation 30 (4), 278-290.
Rauch, A., Frese, M., 2000. Psychological Approaches to Entrepreneurial Success: A General Model and an Overview of Findings, International Review of Industrial and Organizational Psychology 15, 101-142.
Rauch, A., Frese, M., 2007. Let's Put the Person Back into Entrepreneurship Research: A Meta-Analysis on the Relationship between Business Owners' Personality Traits, Business Creation, and Success, European Journal of Work & Organizational Psychology 16 (4), 353-385.
Remenyi, D., Williams, B., Money, A., Swartz, E., 1998. Doing Business Research in Business and Management.
Remenyi, D., 1998. Doing Research in Business and Management: An Introduction to Process and Method. Sage.
Reynolds, P., Gartner, W.B., Greene, P., Cox, L., Carter, N.M., 2002. The Entrepreneur Next Door: Characteristics of Individuals Starting Companies in America: An Executive Summary of the Panel Study of Entrepreneurial Dynamics.
Reynolds, P.D., Hay, M., Camp, S.M., 1999. Global Entrepreneurship Monitor, Babson College.
Reynolds, P.D., 2011. Informal and Early Formal Financial Support in the Business Creation Process: Exploration with PSED II Data Set, Journal of Small Business Management 49 (1), 27-54.
Rideout, E.C., Gray, D.O., 2013. Does Entrepreneurship Education really Work? A Review and Methodological Critique of the Empirical Literature on the Effects of
University‐Based Entrepreneurship Education, Journal of Small Business Management 51 (3), 329-351.
Ripsas, S., 1998. Towards an Interdisciplinary Theory of Entrepreneurship, Small Business Economics 10 (2), 103-115.
Robertson, M., Collins, A., Medeira, N., Slater, J., 2003. Barriers to Start-Up and their Effect on Aspirant Entrepreneurs, Education Training 45 (6), 308-316.
Robinson, P.B., Hunt, H.K., 1992. Entrepreneurship and Birth Order: Fact Or Folklore, Entrepreneurship & Regional Development 4 (3), 287-298.
Robinson, P.B., Stimpson, D.V., Huefner, J.C., Hunt, H.K., 1991. An Attitude Approach to the Prediction of Entrepreneurship, Entrepreneurship Theory and Practice 15 (4), 13-32.
Robinson, P.B., Sexton, E.A., 1994. The Effect of Education and Experience on Self-Employment Success, Journal of Business Venturing 9 (2), 141-156.
284
Rønning, L., 2006. Book Review: The Creation and Destruction of Social Capital: Entrepreneurship, Co-Operative Movements and Institutions, International Small Business Journal 24 (2), 214.
Ronstadt, R., 1990. The Educated Entrepreneurs: A New Era of Entrepreneurial Education is Beginning, Kent, CA, Entrepreneurship Education.Current Developments, Future Directions, 69-88.
Rorty, R., 1990. Pragmatism as Anti-Representationalism, Pragmatism: From Pierce to Davidson.Westview Press, Boulder, CO, 1-6.
Rose, A.M., 1962. A Systematic Summary of Symbolic Interaction Theory, Human Behavior and Social Processes, 3-19.
Rossman, G.B., Wilson, B.L., 1985. Numbers and Words Combining Quantitative and Qualitative Methods in a Single Large-Scale Evaluation Study, Evaluation Review 9 (5), 627-643.
Rotefoss, B., Kolvereid, L., 2005. Aspiring, Nascent and Fledgling Entrepreneurs: An Investigation of the Business Start-Up Process, Entrepreneurship & Regional Development 17 (2), 109-127.
Rotter, J.B., 1966. Generalized Expectancies for Internal Versus External Control of Reinforcement. Psychological Monographs: General and Applied 80 (1), 1.
Roy, W.G., 1997. Socializing Capital. Cambridge Univ Press. Rucker, D.D., Preacher, K.J., Tormala, Z.L., Petty, R.E., 2011. Mediation Analysis in
Social Psychology: Current Practices and New Recommendations, Social and Personality Psychology Compass 5 (6), 359-371.
Sala-I-Martin, X., Bilbao-Osorio, B., Blanke, J., Hanouz, M.D., Geiger, T., 2012. The Global Competitiveness Index 2011–2012: Setting the Foundations for Strong Productivity.
Sánchez, J.C., 2013. The Impact of an Entrepreneurship Education Program on Entrepreneurial Competencies and Intention, Journal of Small Business Management 51 (3), 447-465.
Sarasvathy, S.D., 2001. Causation and Effectuation: Toward a Theoretical Shift from Economic Inevitability to Entrepreneurial Contingency, Academy of Management Review , 243-263.
Sarasvathy, S.D., Venkataraman, S., 2011. Entrepreneurship as Method: Open Questions for an Entrepreneurial Future, Entrepreneurship Theory and Practice 35 (1), 113-135.
SARUA, 2012. Southern African Regional Universities Association, Zambia Data Profile Higher Education Landscape, SARUA Report Accessed on 20 July 2013 http://www.sarua.org/files/country%20reports%202012/zambia%20data%20profile%20eng.pdf.
Saunders, M., Lewis, P., Thornhill, A., 2009. Research Methods for Business Students. Prentice Hall.
Saunders, M.N., Saunders, M., Lewis, P., Thornhill, A., 2012. Research Methods for Business Students, 6/E. Pearson Education India.
Say, J.B., 1821. Letters to Thomas Robert Malthus on Political Economy and Stagnation of Commerce, History of Economic Thought Books.
Say, J.B., Richter, J., 1816. Catechism of Political Economy: Or, Familiar Conversations on the Manner in which Wealth is Produced, Distributed, and Consumed in Society. Printed for Sherwood, Neely, and Jones.
Schein, E.H., 1996. Career Anchors Revisited: Implications for Career Development in the 21st Century, The Academy of Management Executive (1993-2005), 80-88.
Schenkel, M.T., Hechavarria, D.M., Matthews, C.H., 2009. The Role of Human and Social Capital and Technology in Nascent Ventures, New Firm Creation in the United States, 157-183.
Scherer, R.F., Brodzinski, J.D., Wiebe, F.A., 1990. Entrepreneur Career Selection and Gender: A Socialization Approach, Journal of Small Business Management 28 (2), 37-44.
Scherer, R.F., Adams, J.S., Carley, S.S., Wiebe, F.A., 1989. Role Model Performance Effects on Development of Entrepreneurial Career Preference, Entrepreneurship: Theory & Practice 13 (3), 53-71.
285
Schlaegel, C., Koenig, M., 2014. Determinants of Entrepreneurial Intent: A Meta-Analytic Test and Integration of Competing Models, Entrepreneurship Theory and Practice 38 (2), 291-332.
Schramm, C.J., 2006. The Entrepreneurial Imperative: How America's Economic Miracle Will Reshape the World (and Change Your Life). Collins New York.
Schultz, T.W., 1975. The Value of the Ability to Deal with Disequilibria, Journal of Economic Literature 13 (3), 827-846.
Schultz, T.W., 1979. Concepts of Entrepreneurship and Agricultural Research, Kaldor Memorial Lecture, Iowa State University.
Schultz, T.W., Schultz, T.W., 1982. Investing in People: The Economics of Population Quality. Univ of California Press.
Schultz, T., W., 1982. Investment in Entrepreneurial Ability, Scandinavian Journal of Economics 4, 437-448.
Schumpeter, J., Backhaus, U., 1934. The Theory of Economic Development, Joseph Alois Schumpeter , 61-116.
Schumpeter, J.A., 1954. History of Economic Analysis. Psychology Press. Schumpeter, J.A., 1934. Change and the Entrepreneur, Essays of JA Schumpeter. Schutz, A., 1970. Alfred Schutz on Phenomenology and Social Relations. University of
Chicago Press. Schutz, A., 1962. Collected Papers, Vol. I: The Problem of Social Reality, The Hague:
Martinus Nijhoff. Scott, W.R., 1995. Organizations and Institutions. Scott, W., 2008. Approaching Adulthood: The Maturing of Institutional Theory, Theory &
Society 37 (5), 427-442. Segal, G., Borgia, D., Schoenfeld, J., 2005. The Motivation to Become an Entrepreneur,
International Journal of Entrepreneurial Behaviour & Research 11 (1), 42-57. Sexton, D.L., Kent, C.A., 1981. Female Executives Versus Female Entrepreneurs'. In:
Frontiers of Entrepreneurship Research: The Proceeding of the 1981 Babson Conference on Entrepreneurship Research, Wellesley MA: Babson College, pp. 40-45.
Sexton, D.L., Smilor, R.W., 1986. The Art and Science of Entrepreneurship, University of Illinois at Urbana-Champaign's Academy for Entrepreneurial Leadership Historical Research Reference in Entrepreneurship.
Shane, S., Venkataraman, S., 2000. The Promise of Enterpreneurship as a Field of Research, Academy of Management Review, 217-226.
Shane, S.A., 2004. Academic Entrepreneurship: University Spinoffs and Wealth Creation. Edward Elgar Publishing.
Shane, S.A., 2003. A General Theory of Entrepreneurship: The Individual-Opportunity Nexus. Edward Elgar Pub.
Shapero, A., 1981. Why Don'T Your Kids Want to be Entrepreneurs? Inc, September . Shapero, A., 1975. The Displaced, Uncomfortable Entrepreneur, Psychology Today
(November), 83-88. Shapero, A., Sokol, L., 1982. The Social Dimensions of Entrepreneurship. Shaver, K.G., Scott, L.R., 1991. Person, Process, Choice: The Psychology of New
Venture Creation, Entrepreneurship Theory and Practice 16 (2), 23-45. Shepherd, D.A., 2011. Multilevel Entrepreneurship Research: Opportunities for Studying
Entrepreneurial Decision Making, Journal of Management 37 (2), 412-420. Shepherd, D.A., DeTienne, D.R., 2005. Prior Knowledge, Potential Financial Reward, and
Opportunity Identification, Entrepreneurship Theory and Practice 29 (1), 91-112. Shinnar, R.S., Giacomin, O., Janssen, F., 2012. Entrepreneurial Perceptions and
Intentions: The Role of Gender and Culture, Entrepreneurship Theory and Practice 36 (3), 465-493.
Shook, C.L., Priem, R.L., McGee, J.E., 2003. Venture Creation and the Enterprising Individual: A Review and Synthesis, Journal of Management 29 (3), 379-399.
Shrout, P.E., Bolger, N., 2002. Mediation in Experimental and Nonexperimental Studies: New Procedures and Recommendations. Psychological Methods 7 (4), 422.
286
Shuman, J.C., Sussman, G., Shaw, J.J., 1985. «Business Plans and the Start-Up of Rapid-Growth Companies», J.Hornaday, E.Shils, J.Timmons Et K.Vesper (Éd.), Frontiers of Entrepreneurship Research, 294-313.
Silva, M.J., Trigo, V., Antunes, R., 2011. Institutional Approach and Enterprise Creation: Support Systems in the Case of Small City in Rural and Peripheral Areas of Portugal, Economic Interferance 13, 29.
Siu, W., Lo, E.S., 2013. Cultural Contingency in the Cognitive Model of Entrepreneurial Intention, Entrepreneurship Theory and Practice 37 (2), 147-173.
Siwale, J.N., 2006. The Role of Loan Officers and Clients in the Diffusion of Microfinance: A Study of PRIDE Zambia and CETZAM in Zambia. PhD Thesis, Dhuram, UK
Small Business Charter, 2014. Small Business Charter, UK, http://smallbusinesscharter.org/about/why/ accessed 19.04.2014
Smiles, S., 1859. Self-Help. 1859, London 38, 39. Smith, A., 1776. An Inquiry into the Nature and Causes of the Wealth of Nations,(1776),
New York: Modern Library. Smith, K., Beasley, M., 2011. Graduate Entrepreneurs: Intentions, Barriers and Solutions,
Education Training 53 (8/9), 722-740. Sobel, M.E., 1982. Asymptotic Confidence Intervals for Indirect Effects in Structural
Equation Models, Sociological Methodology 13 (1982), 290-312. Solesvik, M., Westhead, P., Matlay, H., Parsyak, V.N., 2013. Entrepreneurial Assets and
Mindsets: Benefit from University Entrepreneurship Education Investment, Education Training 55 (8/9), 2-2.
Solomon, G., 2007. An Examination of Entrepreneurship Education in the United States, Journal of Small Business and Enterprise Development 14 (2), 168-182.
Solomon, G.T., Duffy, S., Tarabishy, A., 2002. The State of Entrepreneurship Education in the United States: A Nationwide Survey and Analysis.
Solomon, G.T., Winslow, E.K., 1988. Toward a Descriptive Profile of the Entrepreneur. The Journal of Creative Behavior.
Soriano, D.R., 2009. Handbook of Research in Entrepreneurship Education, Academy of Management Learning & Education 8 (2), 305-308.
Souitaris, V., Zerbinati, S., Al-Laham, A., 2007. Do Entrepreneurship Programmes Raise Entrepreneurial Intention of Science and Engineering Students? The Effect of Learning, Inspiration and Resources, Journal of Business Venturing 22 (4), 566-591.
Spencer, J.W., Gomez, C., 2004. The Relationship among National Institutional Structures, Economic Factors, and Domestic Entrepreneurial Activity: A Multicountry Study, Journal of Business Research 57 (10), 1098-1107.
Stanworth, M.J.K., Curran, J., 1973. Management Motivation in the Smaller Business. Gower Press.
Steel, P., König, C.J., 2006. Integrating Theories of Motivation, Academy of Management Review 31 (4), 889-913.
Steers, R.M., Braunstein, D.N., 1976. A Behaviorally-Based Measure of Manifest Needs in Work Settings, Journal of Vocational Behavior 9 (2), 251-266.
Stenholm, P., Acs, Z.J., Wuebker, R., 2013. Exploring Country-Level Institutional Arrangements on the Rate and Type of Entrepreneurial Activity, Journal of Business Venturing 28 (1), 176-193.
Stevenson, H.H., Jarillo, J.C., 1990. A Paradigm of Entrepreneurship: Entrepreneurial Management. Springer.
Stewart Jr, W.H., Roth, P.L., 2001. Risk Propensity Differences between Entrepreneurs and Managers: A Meta-Analytic Review. Journal of Applied Psychology 86 (1), 145.
Stewart, W., 1996. Psychological Correlates of Entrepreneurship. New York. Storey, D.J., 2000. Six Steps to Heaven: Evaluating the Impact of Public Policies to
Support Small Business in Developed Economies, in: Sexton, D.L., Landstrom, H. (Eds.), The Blackwell Handbook of Entrepreneurship. Blackwell, Oxford, pp. 176-193.
Stumpf, S., Dunbar, R., Mullen, T., 1991. Simulations in Entrepreneurship Education: Oxymoron Or Untapped Opportunity, Frontiers of Entrepreneurship Research 11, 681-694.
Sullivan, R., 2000. Entrepreneurial Learning and Mentoring, International Journal of Entrepreneurial Behaviour & Research 6 (3), 160-175.
287
Szyliowicz, D., Galvin, T., 2010. Applying Broader Strokes: Extending Institutional Perspectives and Agendas for International Entrepreneurship Research, International Business Review 19 (4), 317-332.
Tabachnick, B.G., Fidell, L., 2012. Using Multivariate Statistics: International Edition. Pearson.
Tashakkori, A., Teddlie, C., 2010. Sage Handbook of Mixed Methods in Social & Behavioral Research. Sage.
Tashakkori, A., Teddlie, C., 1998. Mixed Methodology: Combining Qualitative and Quantitative Approaches. SAGE Publications, Incorporated.
Taylor, D.S., 2006. Culture and Customs of Zambia. Greenwood Press, Westport, USA. Taylor, A.B., MacKinnon, D.P., Tein, J., 2008. Tests of the Three-Path Mediated Effect,
Organizational Research Methods 11 (2), 241-269. Tegtmeir, S., 2012. Evaluating Introductory Lectures in Entrepreneurship: Empirical
Implications Based on the Theory of Planned Behaviour, International Review of Entrepreneurship 10 (1).
Tendler, J., 2002. Small Firms, the Informal Sector, and the Devil's Deal, IDS Bulletin 33 (3), 1-15.
The Economist, 2014. State Capitalism in the Dock; the Performance of State Owned Enterprises has been Shockingly Bad
Thompson, E.R., 2009. Individual Entrepreneurial Intent: Construct Clarification and Development of an Internationally Reliable Metric, Entrepreneurship Theory and Practice 33 (3), 669-694.
Thurstone, L.L., 1947. Multiple-Factor Analysis; a Development and Expansion of the Vectors of Mind.
Timmons, J.A., Muzyka, D.F., Stevenson, H.H., Bygrave, W.D., 1987. Opportunity Recognition: The Core of Entrepreneurship, Frontiers of Entrepreneurship Research 109, 123.
Tkachev, A., Kolvereid, L., 1999. Self-Employment Intentions among Russian Students, Entrepreneurship & Regional Development 11 (3), 269-280.
Tonelli, M., Dalglish, C.L., 2011. Entrepreneurial Becoming: An Educational Pathway Out of Poverty.
Trice, A.D., 1991. Stability of Children's Career Aspirations, The Journal of Genetic Psychology 152 (1), 137-139.
Turgot, A.R.J., 1766. Baron De l’Aulne (1766), Reflections on the Formation and Distribution of Riches.
Ucbasaran, D., Westhead, P., Wright, M., 2008. Opportunity Identification and Pursuit: Does an Entrepreneur’s Human Capital Matter? Small Business Economics 30 (2), 153-173.
Ucbasaran, D., Westhead, P., Wright, M., Binks, M., 2003. Does Entrepreneurial Experience Influence Opportunity Identification? The Journal of Private Equity 7 (1), 7-14.
Uhlmann, E., Swanson, J., 2004. Exposure to Violent Video Games Increases Automatic Aggressiveness, Journal of Adolescence 27 (1), 41-52.
UKBI, 2014. United Kingdom Business Incubation Association, http://www.ukbi.co.uk/resources/business-incubation.aspx accessed 22.04.2014.
Unger, J.M., Rauch, A., Frese, M., Rosenbusch, N., 2011. Human Capital and Entrepreneurial Success: A Meta-Analytical Review, Journal of Business Venturing 26 (3), 341-358.
van Burg, E., Romme, A.G.L., 2014. Creating the Future Together: Toward a Framework for Research Synthesis in Entrepreneurship, Entrepreneurship Theory and Practice.
Van der Sijde, P., 2008. Teaching Entrepreneurship: Cases for Education and Training. Springer.
Van Stel, A., Storey, D.J., Thurik, A.R., 2007. The Effect of Business Regulations on Nascent and Young Business Entrepreneurship, Small Business Economics 28 (2-3), 171-186.
Vanevenhoven, J., Liguori, E., 2013. The Impact of Entrepreneurship Education: Introducing the Entrepreneurship Education Project, Journal of Small Business Management 51 (3), 315-328.
288
Veciana, J.M., Urbano, D., 2008. The Institutional Approach to Entrepreneurship Research. Introduction, International Entrepreneurship and Management Journal 4 (4), 365-379.
Veciana, J.M., Aponte, M., Urbano, D., 2005. University Students’ Attitudes Towards Entrepreneurship: A Two Countries Comparison, The International Entrepreneurship and Management Journal 1 (2), 165-182.
Verheul, I., Wennekers, S., Audretsch, D., Thurik, R., 2002. An Eclectic Theory of Entrepreneurship: Policies, Institutions and Culture, Entrepreneurship: Determinants and Policy in a European-US Comparison, 11-81.
Verheul, I., Thurik, R., Grilo, I., van der Zwan, P., 2012. Explaining Preferences and Actual Involvement in Self-Employment: Gender and the Entrepreneurial Personality, Journal of Economic Psychology 33 (2), 325-341.
Volery, T., Müller, S., Oser, F., Naepflin, C., del Rey, N., 2013. The Impact of Entrepreneurship Education on Human Capital at Upper-Secondary Level, Journal of Small Business Management 51 (3), 429-446.
von Graevenitz, G., Harhoff, D., Weber, R., 2010. The Effects of Entrepreneurship Education, Journal of Economic Behavior & Organization 76 (1), 90-112.
Vroom, V.H., 1964. Work and Motivation, 1964, NY: John Wiley &sons, 47-51. Walras, L., Jaffé, W., 1898. Elements of Pure Economics, Or, the Theory of Social
Wealth, Published in 1984 ed. Orion Editions Philadelphia. Walter, S.G., Parboteeah, K.P., Walter, A., 2011. University Departments and
Self‐Employment Intentions of Business Students: A Cross‐Level Analysis, Entrepreneurship Theory and Practice.
Wang, C.L., Chugh, H., 2014. Entrepreneurial Learning: Past Research and Future Challenges, International Journal of Management Reviews 16 (1), 24-61.
Wang, Y., Ahmed, P.K., 2009. The Moderating Effect of the Business Strategic Orientation on eCommerce Adoption: Evidence from UK Family Run SMEs, The Journal of Strategic Information Systems 18 (1), 16-30.
Webb, E.J., Campbell, D.T., Schwartz, R.D., Sechrest, L., 1966. Unobtrusive Methods: Nonreactive Research in the Social Sciences.
Weber, M., 1947. The Theory of Economic and Social Organization, Trans.AM Henderson and Talcott Parsons.New York: Oxford University Press.
Webster, F.A., 1977. Entrepreneurs and Ventures: An Attempt at Classification and Clarification, Academy of Management Review 2 (1), 54-61.
Wegner, D.M., 2002. The Illusion of Conscious Will. MIT press. Welter, F., Smallbone, D., 2011. Institutional Perspectives on Entrepreneurial Behavior in
Challenging Environments, Journal of Small Business Management 49 (1), 107-125. Wennekers, S., Thurik, R., 1999. Linking Entrepreneurship and Economic Growth, Small
Business Economics 13 (1), 27-56. Wennekers, S., Van Wennekers, A., Thurik, R., Reynolds, P., 2005. Nascent
Entrepreneurship and the Level of Economic Development, Small Business Economics 24 (3), 293-309.
Whitehead, A.N., 1967. Aims of Education. Simon and Schuster. Wicks, D., 2001. Institutionalized Mindsets of Invulnerability: Differentiated Institutional
Fields and the Antecedents of Organizational Crisis, Organization Studies 22 (4), 659-692.
Williams, C.C., 2009. The Motives of Off-the-Books Entrepreneurs: Necessity-Or Opportunity-Driven? International Entrepreneurship and Management Journal 5 (2), 203-217.
Williams, S., Turnbull, A., 1997. First Moves into Entrepreneurship Teaching in Scottish Universities; a Consortium Approach, The Robert Gordon University.
Williamson, N., Beadle, S., Charalambous, S., 2013. Enterprise Education Impact in Higher Education and further Education in UK.
Wilson, D., Sperber, D., 1992. Relevance Theory. Wiley Online Library. Wilson, K., Vyakarnam, S., Volkmann, C., Mariotti, S., Rabuzzi, D., 2009. Educating the
Next Wave of Entrepreneurs: Unlocking Entrepreneurial Capabilities to Meet the Global Challenges of the 21st Century. In: World Economic Forum: A Report of the Global Education Initiative, April 2009.
289
Wilson, F., Kickul, J., Marlino, D., 2007. Gender, Entrepreneurial Self-Efficacy, and Entrepreneurial Career Intentions: Implications for Entrepreneurship Education, Entrepreneurship: Theory & Practice 31 (3), 387-406.
Witty, A., 2013. Encouraging a British Invention Revolution: Sir Andrew Witty's Review of Universities and Growth, http://smallbusinesscharter.org/images/media/mediasbsc_-_andrew_witty_report_-_147_pps.pdf accessed 24.04.2014.
Wood, R.E., Goodman, J.S., Beckmann, N., Cook, A., 2008. Mediation Testing in Management Research A Review and Proposals, Organizational Research Methods 11 (2), 270-295.
Woodier-Harris, N.R., 2010. Evaluating the Impact of SPEED on Students' Career Choices: A Pilot Study, Education Training 52 (6/7), 463-476.
Woodruff, C., 2001. Review of De Soto's" the Mystery of Capital". Wooldridge, J., 2012. Introductory Econometrics: A Modern Approach. Cengage Learning. Wooldridge, J.M., 2010. Econometric Analysis of Cross-Sectional&Panel Data. MIT press. Wooten, K.C., Timmerman, T.A., Folger, R., 1999. The use of Personality and the Five-
Factor Model to Predict New Business Ventures: From Outplacement to Start-Up, Journal of Vocational Behavior 54 (1), 82-101.
World Bank, 2014. Country Data for Zambia, http://www.worldbank.org/en/country/zambia accessed july 13, 2014 18:00 Hours UK Time.
World Bank, 2013. Zambia's Job Challenge, Realities on the Ground, World Bank Zambia Economic Brief.
World Bank, 2012. Doing Business 2013: Smarter Regulations for Small and Medium-Size Enterprises. World Bank Publications.
Wu, S., Wu, L., 2008. The Impact of Higher Education on Entrepreneurial Intentions of University Students in China, Journal of Small Business and Enterprise Development 15 (4), 752-774.
Wu, S.Y., 1989. Production, Entrepreneurship, and Profits. Basil Blackwell Oxford. Wu, A., Zumbo, B., 2008. Understanding and using Mediators and Moderators, Social
Indicators Research 87 (3), 367-392. Zahra, S.A., 1993. Environment, Corporate Entrepreneurship, and Financial Performance:
A Taxonomic Approach, Journal of Business Venturing 8 (4), 319-340. Zahra, S.A., Covin, J.G., 1995. Contextual Influences on the Corporate Entrepreneurship-
Performance Relationship: A Longitudinal Analysis, Journal of Business Venturing 10 (1), 43-58.
Zellweger, T., Sieger, P., Halter, F., 2011. Should I Stay Or should I Go? Career Choice Intentions of Students with Family Business Background, Journal of Business Venturing 26 (5), 521-536.
Zhang, Y., Duysters, G., Cloodt, M., 2013. The Role of Entrepreneurship Education as a Predictor of University Students’ Entrepreneurial Intention, International Entrepreneurship and Management Journal, 1-19.
Zhao, H., Seibert, S.E., 2006. The Big Five Personality Dimensions and Entrepreneurial Status: A Meta-Analytical Review. Journal of Applied Psychology 91 (2), 259.
Zhao, H., Seibert, S.E., Lumpkin, G.T., 2010a. The Relationship of Personality to Entrepreneurial Intentions and Performance: A Meta-Analytic Review, Journal of Management 36 (2), 381-404.
Zhao, X., Lynch, J.G., Chen, Q., 2010b. Reconsidering Baron and Kenny: Myths and Truths about Mediation Analysis, Journal of Consumer Research 37 (2), 197-206.
Zhao, H., Seibert, S.E., Hills, G.E., 2005. The Mediating Role of Self-Efficacy in the Development of Entrepreneurial Intentions, Journal of Applied Psychology 90 (6), 1265-1272.
Zhou, Z., Cal, L., 2010. On the Periodical Development of Technical Education,
Vocational and Entrepreneurship Training in Zambia, Studies in Foreign Education 12
(12), 163-183.
290
APPENDICES
Appendix 2.11- Map of Zambia in the Context of Africa
Source: http://www.worldatlas.com/webimage/countrys/africa/zm.htm, March 18, 2014 14:00hrs UK
291
Appendix 7.12- Ethical Approval Notification- Interviews
292
Appendix 7.23-Ethical Approval Notification-Survey
293
Appendix 7.34- Letter of Introduction to Vice Chancellors at Zambian Universities
294
Appendix 7.45- Interview Questionnaire
295
296
297
Appendix 7.56- Survey Questionnaire
298
299
300
301
302
303
Appendix 9.17- Cross Tabulation of Age Groups by University Type
Private or Public University * Age Group 25, 30,35, above 35 Cross-tabulation
Age Group 25, 30,35, above 35 Total
25 years and below
26 to 30 years
31 -35 years
36 years and above
Private or Public
University
Private
Count 120 36 14 19 189
% within Private or Public University
63.2% 19.2% 7.4% 10.3% 100.0%
% within Age Group 25, 30,35, above 35
40.4% 51.4% 63.6% 46.4% 44.0%
% of Total 27.8% 8.4% 3.2% 4.5% 44.0%
Public
Count 177 35 8 23 243
% within Private or Public University
73.1% 14.3% 3.3% 9.3% 100.0%
% within Age Group 25, 30,35, above 35
59.6% 48.6% 36.4% 53.6% 56.0%
% of Total 41.0% 8.0% 1.9% 5.2% 56.0%
Total
Count 297 71 22 42 432
% within Private or Public University
68.8% 16.4% 5.1% 9.7% 100.0%
% within Age Group 25, 30,35, above 35
100.0% 100.0% 100.0% 100.0% 100.0%
% of Total 68.8% 16.4% 5.1% 9.7% 100.0%
Appendix 9.28- ANOVA Tests on Age Differences in EI and Attitudes
Note: required assumption of homogeneity of variance between groups for ANOVA to proceed based on the insignificant (p>0.05) Levene’s statistic (Pallant, 2010; Burns and Burns, 2008).
Appendix 9.39- Means and Standard Deviations for Age groups and EI
304
Appendix 9.410- Post-Hoc Tests on EI Differences across Age Groups
* The mean difference is significant at the 0.05 level.
Appendix 9.511- Post-Hoc Tests for Differences in Employment and Self-Employment Experience Across Age Groups
* The mean difference is significant at the 0.05 level.
Dependent Variable (I) Age Group (J) Age Group Mean DifferenceSig.
(I-J)
EntrepreneurialIntention 25 years and below 26 to 30 years 0.0741 0.799
31 -35 years 0.21444 0.389
36 years and above 0.01909 0.998
26 to 30 years 25 years and below -0.0741 0.799
31 -35 years 0.14034 0.785
36 years and above -0.05501 0.968
31 -35 years 25 years and below -0.21444 0.389
26 to 30 years -0.14034 0.785
36 years and above -0.19535 0.620
36 years and above 25 years and below -0.01909 0.998
26 to 30 years 0.05501 0.968
31 -35 years 0.19535 0.620
Feasibility 25 years and below 26 to 30 years -.27290* 0.007
31 -35 years -.38637* 0.033
36 years and above -0.11198 0.721
26 to 30 years 25 years and below .27290* 0.007
31 -35 years -0.11348 0.887
36 years and above 0.16092 0.576
31 -35 years 25 years and below .38637* 0.033
26 to 30 years 0.11348 0.887
36 years and above 0.27439 0.367
36 years and above 25 years and below 0.11198 0.721
26 to 30 years -0.16092 0.576
31 -35 years -0.27439 0.367
Desirability 25 years and below 26 to 30 years -0.05457 0.909
31 -35 years 0.03908 0.992
36 years and above 0.06394 0.923
26 to 30 years 25 years and below 0.05457 0.909
31 -35 years 0.09365 0.924
36 years and above 0.11851 0.757
31 -35 years 25 years and below -0.03908 0.992
26 to 30 years -0.09365 0.924
36 years and above 0.02486 0.999
36 years and above 25 years and below -0.06394 0.923
26 to 30 years -0.11851 0.757
31 -35 years -0.02486 0.999
SubjectiveNorms 25 years and below 26 to 30 years 0.06535 0.875
31 -35 years 0.1286 0.807
36 years and above .43878* 0.000
26 to 30 years 25 years and below -0.06535 0.875
31 -35 years 0.06325 0.979
36 years and above .37343* 0.019
31 -35 years 25 years and below -0.1286 0.807
26 to 30 years -0.06325 0.979
36 years and above 0.31019 0.272
36 years and above 25 years and below -.43878* 0.000
26 to 30 years -.37343* 0.019
31 -35 years -0.31019 0.272
Dependent Variable (I) Age Group (J) Age Group Mean DifferenceSig.
(I-J)
Employment experience25 years and below 26 to 30 years -1.75645* 0.000
Length 31 -35 years -8.14041* 0.000
36 years and above -15.73797* 0.000
26 to 30 years 25 years and below 1.75645* 0.000
31 -35 years -6.38396* 0.000
36 years and above -13.98152* 0.000
31 -35 years 25 years and below 8.14041* 0.000
26 to 30 years 6.38396* 0.000
36 years and above -7.59756* 0.000
36 years and above 25 years and below 15.73797* 0.000
26 to 30 years 13.98152* 0.000
31 -35 years 7.59756* 0.000
Self employment 25 years and below 26 to 30 years -.55130* 0.004
Length 31 -35 years -2.26288* 0.000
36 years and above -1.49460* 0.000
26 to 30 years 25 years and below .55130* 0.004
31 -35 years -1.71158* 0.000
36 years and above -.94329* 0.000
31 -35 years 25 years and below 2.26288* 0.000
26 to 30 years 1.71158* 0.000
36 years and above 0.76828 0.081
36 years and above 25 years and below 1.49460* 0.000
26 to 30 years .94329* 0.000
31 -35 years -0.76828 0.081
305
Appendix 9.612- EE Mediating the Influence of Normative Institution on Desirability
Appendix 9.713- EE Mediating the Influence of Cognitive Institution on Feasibility
Appendix 9.814- EE Mediating the Influence of Cognitive Institution on Desirability
Models 1 & 2 Mediator: Perceived Learning Mediator: Practical Approaches Mediator:Access to Resources
Dependent
Variable=
Desirability Model assessments (1) Model assessments (2) Model assessments (3)
Variables B(1) t (1) Sig. (1) F (sig), R, R sq, Rsq adj. B(2) t (2) Sig.(2) F (sig), R, R sq, R sq adj. B(3) t (3) Sig. (3) F (sig), R, R sq, R sq adj.
1 (Constant) 3.530 23.267 0.000 F=21.754 (p=0.000) 3.530 23.189 0.000 F=21.609(p=0.000) 3.530 23.163 0.000 F=21.560(p=0.000)
Normative(c) 0.186 4.664 0.000 R=0.215, Rsq=0.046 0.186 4.648 0.000 R=0.215, Rsq=0.046 0.186 4.643 0.000 R=0.215, Rsq=0.046
Rsq adj=0.044 Rsq adj=0.044 Rsq adj=0.044
2 (Constant) 2.351 10.788 0.000 F=38.017 (p=0.000) 3.267 19.943 0.000 F=18.984(p=0.000) 3.356 18.528 0.000 F=12.392(p=0.000)
Normative(c') 0.108 2.748 0.006 FΔ (51.813, p=0.000) 0.137 3.317 0.001 FΔ (15.648, p=0.000) 0.163 3.869 0.000 FΔ (3.122, p=0.078)
Mediator (b) 0.350 7.198 0.000 R=0.381, Rsq=0.145 0.145 3.956 0.000 R=0.281, Rsq=0.079 0.080 1.767 0.078 R=0.230, Rsq=0.053
Rsq adj=0.142 Rsq adj=0.075 Rsq adj=0.049
3 (Constant) 3.372 24.109 0.000 F=36.787 (p=0.000) 1.815 9.349 0.000 F=44.221(p=0.000) 2.162 13.647 0.000 F=48.044(p=0.000)
Normative(a) 0.223 6.065 0.000 R=0.275, Rsq=0.076 0.340 6.650 0.000 R=0.301, Rsq=0.090 0.289 6.931 0.000 R=0.312, Rsq=0.098
Rsq adj=0.074 Rsq adj=0.088 Rsq adj=0.096
Sobel test (ab) B1 Z Sig. B2 Z Sig. B3 Z Sig.
Mediation 0.075 3.761 0.000 0.047 3.067 0.002 0.022 1.541 0.123
Type (abc') 0.0084 Complementary 0.007 Complementary Direct only non-mediation
M
o
d
e
l
Models 1 & 2 Mediator: Perceived Learning Mediator: Practical Approaches Mediator:Access to Resources
Dependent
Variable=
Feasibility Model assessments (1) Model assessments (2) Model assessments (3)
Variables B(1) t (1) Sig. (1) F (sig), R, R sq, Rsq adj. B(2) t (2) Sig.(2) F (sig), R, R sq, R sq adj. B(3) t (3) Sig. (3) F (sig), R, R sq, R sq adj.
1 (Constant) 3.050 26.499 0.000 F=16.827 (p=0.000) 3.050 26.410 0.000 F=16.714(p=0.000) 3.050 26.410 0.000 F=16.714(p=0.000)
Cognitive(c) 0.173 4.102 0.000 R=0.190, Rsq=0.036 0.173 4.088 0.000 R=0.190, Rsq=0.036 0.173 4.088 0.000 R=0.190, Rsq=0.036
Rsq adj=0.034 Rsq adj=0.034 Rsq adj=0.034
2 (Constant) 1.451 6.570 0.000 F=44.014 (p=0.000) 2.529 17.600 0.000 F=25.558 (p=0.000) 2.352 13.740 0.000 F=23.416 (p=0.000)
Cognitive(c') 0.134 3.377 0.001 FΔ (68.655, p=0.000) 0.121 2.887 0.004 FΔ (33.191, p=0.000) 0.141 3.390 0.001 FΔ (29.061, p=0.000)
Mediator (b) 0.406 8.286 0.000 R=0.406, Rsq=0.165 0.214 5.761 0.000 R=0.322, Rsq=0.103 0.242 5.391 0.000 R=0.309, Rsq=0.096
Rsq adj=0.161 Rsq adj=0.099 Rsq adj=0.092
3 (Constant) 3.944 38.169 0.000 F=6.553 (p=0.011) 2.441 17.187 0.000 F=22.000 (p=0.000) 2.882 24.410 0.000 F=9.561 (p=0.002)
Cognitive(a) 0.097 2.560 0.011 R=0.120, Rsq=0.014 0.245 4.690 0.000 R=0.216, Rsq=0.047 0.134 3.092 0.002 R=0.145, Rsq=0.021
Rsq adj=0.012 Rsq adj=0.046 Rsq adj=0.019
Sobel test (ab) B1 Z Sig. B2 Z Sig. B3 Z Sig.
Mediation 0.041 2.429 0.015 0.054 3.311 0.001 0.034 2.431 0.015
Type (abc') 0.01 complementary 0.006 complementary 0.005 complementary
M
o
d
e
l
Models 1 & 2 Mediator: Perceived Learning Mediator: Practical Approaches Mediator:Access to Resources
Dependent
Variable=
Desirability Model assessments (1) Model assessments (2) Model assessments (3)
Variables B(1) t (1) Sig. (1) F (sig), R, R sq, Rsq adj. B(2) t (2) Sig.(2) F (sig), R, R sq, R sq adj. B(3) t (3) Sig. (3) F (sig), R, R sq, R sq adj.
1 (Constant) 4.190 37.701 0.000 F=0.047 (p=0.829) 4.190 37.575 0.000 F=0.047(p=0.829) 4.190 37.533 0.000 F=0.046(p=0.829)
Cognitive(c) 0.009 0.216 0.829 R=0.010, Rsq=0.00 0.009 0.216 0.829 R=0.010, Rsq=0.00 0.009 0.216 0.829 R=0.010, Rsq=0.00
Rsq adj=-0.002 Rsq adj=-0.002 Rsq adj=-0.002
2 (Constant) 2.649 12.414 0.000 F=34.154 (p=0.000) 3.730 26.723 0.000 F=13.659 (p=0.000) 3.795 22.455 0.000 F=4.796 (p=0.009)
Cognitive(c') -0.029 -0.759 0.448 FΔ (68.255, p=0.000) -0.037 -0.913 0.362 FΔ (27.269, p=0.000) -0.010 -0.232 0.816 FΔ (9.544, p=0.002)
Mediator (b) 0.391 8.262 0.000 R=0.363, Rsq=0.132 0.188 5.222 0.000 R=0.240, Rsq=0.058 0.137 3.089 0.002 R=0.145, Rsq=0.021
Rsq adj=0.128 Rsq adj=0.053 Rsq adj=0.017
3 (Constant) 3.944 38.169 0.000 F=6.553 (p=0.011) 2.441 17.187 0.000 F=22.000 (p=0.000) 2.882 24.410 0.000 F=9.561 (p=0.002)
Cognitive(a) 0.097 2.560 0.011 R=0.120, Rsq=0.014 0.245 4.690 0.000 R=0.216, Rsq=0.047 0.134 3.092 0.002 R=0.145, Rsq=0.021
Rsq adj=0.012 Rsq adj=0.045 Rsq adj=0.019
Sobel test (ab) B1 Z Sig. B2 Z Sig. B3 Z Sig.
Mediation 0.039 2.373 0.018 0.047 3.273 0.001 0.019 2.020 0.043
Type (abc') Indirect only Indirect only Indirect only
M
o
d
e
l
306
Appendix 9.915- EE Mediating the Influence of Regulatory Institution on Feasibility
Appendix 9.1016- EE Mediating the Effect of Regulatory Institution on Desirability
Appendix 9.1117- EE Mediating the Effect of Risk Taking Propensity on Feasibility
Models 1 & 2 Mediator: Perceived Learning Mediator: Practical Approaches Mediator:Access to Resources
Dependent
Variable=
Feasibility Model assessments (1) Model assessments (2) Model assessments (3)
Variables B(1) t (1) Sig. (1) F (sig), R, R sq, Rsq adj. B(2) t (2) Sig.(2) F (sig), R, R sq, R sq adj. B(3) t (3) Sig. (3) F (sig), R, R sq, R sq adj.
1 (Constant) 3.204 25.960 0.000 F=6.082 (p=0.014) 3.204 25.873 0.000 F=6.041 (p=0.014) 3.204 25.873 0.000 F=6.041(p=0.014)
Regulatory (c) 0.117 2.466 0.014 R=0.116, Rsq=0.013 0.117 2.458 0.014 R=0.116, Rsq=0.013 0.117 2.458 0.014 R=0.116, Rsq=0.013
Rsq adj=0.011 Rsq adj=0.011 Rsq adj=0.011
2 (Constant) 1.549 6.828 0.000 F=39.255 (p=0.000) 2.619 17.212 0.000 F=22.280 (p=0.000) 2.483 14.079 0.000 F=18.756(p=0.000)
Regulatory(c') 0.080 1.804 0.072 FΔ (71.47, p=0.000) 0.071 1.532 0.126 FΔ (38.014, p=0.000) 0.079 1.687 0.092 FΔ (31.062, p=0.000)
Mediator (b) 0.417 8.454 0.000 R=0.387, Rsq=0.15 0.228 6.166 0.000 R=0.302, Rsq=0.091 0.253 5.573 0.000 R= 0.279, Rsq=0.078
Rsq adj=0.146 Rsq adj=0.087 Rsq adj=0.074
3 (Constant) 3.972 36.159 0.000 F=4.442 (p=0.036) 2.567 16.839 0.000 F=11.881 (p=0.001) 2.851 22.773 0.000 F=9.964 (p=0.002)
Regulatory (a) 0.089 2.108 0.036 R=0.099, Rsq=0.01 0.202 3.447 0.001 R=0.161, Rsq=0.026 0.152 3.157 0.002 R=0.148,Rsq=0.022
Rsq adj=0.008 Rsq adj=0.024 Rsq adj=0.02
Sobel test (ab) B1 Z Sig. B2 Z Sig. B3 Z Sig.
Mediation 0.037 2.015 0.044 0.046 2.951 0.003 0.038 2.668 0.008
Type (abc') indirect-only indirect-only indirect-only
M
o
d
e
l
Models 1 & 2 Mediator: Perceived Learning Mediator: Practical Approaches Mediator:Access to Resources
Dependent
Variable=
Desirability Model assessments (1) Model assessments (2) Model assessments (3)
Variables B(1) t (1) Sig. (1) F (sig), R, R sq, Rsq adj. B(2) t (2) Sig.(2) F (sig), R, R sq, R sq adj. B(3) t (3) Sig. (3) F (sig), R, R sq, R sq adj.
1 (Constant) 4.186 35.507 0.000 F=0.056 (p=0.812) 4.186 35.388 0.000 F=0.056 (p=0.813) 4.186 35.349 0.000 F=0.056(p=0.813)
Regulatory (c) 0.011 0.237 0.812 R=0.011, Rsq=0.00 0.011 0.237 0.813 R=0.011, Rsq=0.00 0.011 0.236 0.813 R=0.011, Rsq=0.0
Rsq adj=-0.002 Rsq adj=-0.002 Rsq adj=-0.002
2 (Constant) 2.641 12.137 0.000 F=33.929 (p=0.000) 3.712 25.234 0.000 F=13.373 (p=0.000) 3.796 21.988 0.000 F=4.782(p=0.009)
Regulatory(c') -0.024 -0.562 0.575 FΔ (67.793, p=0.000) -0.027 -0.592 0.554 FΔ (26.688, p=0.000) -0.010 -0.220 0.826 FΔ (9.507, p=0.002)
Mediator (b) 0.389 8.234 0.000 R=0.363, Rsq=0.132 0.185 5.166 0.000 R=0.238, Rsq=0.057 0.137 3.083 0.002 R= 0.145, Rsq=0.021
Rsq adj=0.128 Rsq adj=0.052 Rsq adj=0.017
3 (Constant) 3.972 36.159 0.000 F=4.442 (p=0.036) 2.567 16.839 0.000 F=11.881 (p=0.001) 2.851 22.773 0.000 F=9.964 (p=0.002)
Regulatory (a) 0.089 2.108 0.036 R=0.099, Rsq=0.01 0.202 3.447 0.001 R=0.161, Rsq=0.026 0.152 3.157 0.002 R=0.148,Rsq=0.022
Rsq adj=0.008 Rsq adj=0.024 Rsq adj=0.02
Sobel test (ab) B1 Z Sig. B2 Z Sig. B3 Z Sig.
Mediation 0.033 2.017 0.044 0.035 2.791 0.005 0.021 2.215 0.027
Type (abc') Indirect only Indirect only Indirect only
M
o
d
e
l
Models 1 & 2 Mediator: Perceived Learning Mediator: Practical Approaches Mediator:Access to Resources
Dependent
Variable=
Feasibility Model assessments (1) Model assessments (2) Model assessments (3)
Variables B(1) t (1) Sig. (1) F (sig), R, R sq, Rsq adj. B(2) t (2) Sig.(2) F (sig), R, R sq, R sq adj. B(3) t (3) Sig. (3) F (sig), R, R sq, R sq adj.
1 (Constant) 2.292 12.048 0.000 F=41.594(p=0.000) 2.292 12.008 0.000 F=41.315(p=0.000) 2.292 12.008 0.000 F=41.315(p=0.000)
RiskTakingPro(c) 0.321 6.449 0.000 R=0.292, Rsq=0.085 0.321 6.428 0.000 R=0.292, Rsq=0.085 0.321 6.428 0.000 R=0.292, Rsq=0.085
Rsq adj=0.083 Rsq adj=0.083 Rsq adj=0.083
2 (Constant) 1.055 4.331 0.000 F=51.502 (p=0.000) 1.850 9.227 0.000 F=38.016 (p=0.000) 1.816 8.551 0.000 F=32.556(p=0.000)
RiskTakingPro(c') 0.237 4.923 0.000 FΔ (56.267, p=0.000) 0.273 5.576 0.000 FΔ (31.847, p=0.000) 0.267 5.334 0.000 FΔ (21.857, p=0.000)
Mediator (b) 0.369 7.501 0.000 R=0.433, Rsq=0.188 0.202 5.643 0.000 R=0.383, Rsq=0.146 0.210 4.675 0.000 R= 0.358, Rsq=0.128
Rsq adj=0.184 Rsq adj=0.143 Rsq adj=0.124
3 (Constant) 3.347 19.444 0.000 F=25.156 (p=0.000) 2.182 8.951 0.000 F=13.596(p=0.000) 2.268 11.486 0.000 F=24.469(p=0.000)
RiskTakingPro(a) 0.226 5.016 0.000 R=0.231, Rsq=0.053 0.235 3.687 0.000 R=0.172, Rsq=0.030 0.255 4.947 0.000 R=0.229,Rsq=0.052
Rsq adj=0.051 Rsq adj=0.027 Rsq adj=0.050
Sobel test (ab) B1 Z Sig. B1 Z Sig. B3 Z Sig.
Mediation 0.078 3.471 0.001 0.046 2.934 0.003 0.053 3.163 0.002
Type (abc') 0.020 Complementary mediation 0.013 Complementary mediation 0.01 Complementary mediation
M
o
d
e
l
307
Appendix 9.1218- EE Mediating the Effect of Risk Taking Propensity on Desirability
Appendix 9.1319- EE Mediating the Influence of Locus of Control on Feasibility
Appendix 9.1420- EE Mediating the Influence of Locus of Control on Desirability
Models 1 & 2 Mediator: Perceived Learning Mediator: Practical Approaches Mediator:Access to Resources
Dependent
Variable=
Desirability Model assessments (1) Model assessments (2) Model assessments (3)
Variables B(1) t (1) Sig. (1) F (sig), R, R sq, Rsq adj. B(2) t (2) Sig.(2) F (sig), R, R sq, R sq adj. B(3) t (3) Sig. (3) F (sig), R, R sq, R sq adj.
1 (Constant) 2.972 16.594 0.000 F=50.239(p=0.000) 2.972 16.538 0.000 F=49.956(p=0.000) 2.972 16.520 0.000 F=49.844(p=0.000)
RiskTakingPro(c) 0.332 7.092 0.000 R=0.318, Rsq=0.101 0.332 7.068 0.000 R=0.318, Rsq=0.101 0.332 7.060 0.000 R=0.318, Rsq=0.101
Rsq adj=0.099 Rsq adj=0.099 Rsq adj=0.099
2 (Constant) 1.883 8.141 0.000 F=52.049(p=0.000) 2.659 13.870 0.000 F=34.650(p=0.000) 2.811 13.742 0.000 F=26.384(p=0.000)
RiskTakingPro(c') 0.259 5.652 0.000 FΔ (48.475, p=0.000) 0.298 6.370 0.000 FΔ (17.492, p=0.000) 0.314 6.509 0.000 FΔ (2.730, p=0.099)
Mediator (b) 0.325 6.962 0.000 R=0.435, Rsq=0.189 0.144 4.182 0.000 R=0.367, Rsq=0.135 0.071 1.652 0.099 R= 0.326, Rsq=0.106
Rsq adj=0.185 Rsq adj=0.131 Rsq adj=0.102
3 (Constant) 3.347 19.444 0.000 F=25.156 (p=0.000) 2.182 8.951 0.000 F=13.596(p=0.000) 2.268 11.486 0.000 F=24.469(p=0.000)
RiskTakingPro(a) 0.226 5.016 0.000 R=0.231, Rsq=0.053 0.235 3.687 0.000 R=0.172, Rsq=0.030 0.255 4.947 0.000 R=0.229,Rsq=0.052
Rsq adj=0.051 Rsq adj=0.027 Rsq adj=0.050
Sobel test (ab) B1 Z Sig. B1 Z Sig. B3 Z Sig.
Mediation 0.068 3.268 0.001 0.034 2.692 0.007 0.018 1.561 0.118
Type (abc') 0.019 Complementary mediation 0.010 Complementary mediation Direct only non-mediation
M
o
d
e
l
Models 1 & 2 Mediator: Perceived Learning Mediator: Practical Approaches Mediator:Access to Resources
Dependent
Variable=
Feasibility Model assessments (1) Model assessments (2) Model assessments (3)
Variables B(1) t (1) Sig. (1) F (sig), R, R sq, Rsq adj. B(2) t (2) Sig.(2) F (sig), R, R sq, R sq adj. B(3) t (3) Sig. (3) F (sig), R, R sq, R sq adj.
1 (Constant) 2.214 9.584 0.000 F=31.468(p=0.000) 2.214 9.552 0.000 F=31.257(p=0.000) 2.214 9.552 0.000 F=31.257(p=0.000)
LocusOfCont(c) 0.301 5.610 0.000 R=0.256, Rsq=0.066 0.301 5.591 0.000 R=0.256, Rsq=0.066 0.301 5.591 0.000 R=0.256, Rsq=0.066
Rsq adj=0.064 Rsq adj=0.064 Rsq adj=0.064
2 (Constant) 1.282 4.994 0.000 F=42.046 (p=0.000) 1.767 7.477 0.000 F=33.835 (p=0.000) 1.698 6.849 0.000 F=29.213(p=0.000)
LocusOfCont(c') 0.156 2.834 0.005 FΔ (49.229, p=0.000) 0.255 4.843 0.000 FΔ (34.084, p=0.000) 0.252 4.717 0.000 FΔ (25.448, p=0.000)
Mediator (b) 0.369 7.016 0.000 R=0.398, Rsq=0.159 0.210 5.838 0.000 R=0.364, Rsq=0.133 0.225 5.045 0.000 R= 0.341, Rsq=0.117
Rsq adj=0.155 Rsq adj=0.129 Rsq adj=0.113
3 (Constant) 2.526 12.818 0.000 F=73.701 (p=0.000) 2.124 7.222 0.000 F=10.471(p=0.001) 2.292 9.565 0.000 F=15.540(p=0.000)
LocusOfCont(a) 0.393 8.585 0.000 R=0.376, Rsq=0.141 0.221 3.236 0.001 R=0.152, Rsq=0.023 0.220 3.942 0.000 R=0.184,Rsq=0.034
Rsq adj=0.139 Rsq adj=0.021 Rsq adj=0.032
Sobel test (ab) B1 Z Sig. B1 Z Sig. B3 Z Sig.
Mediation 0.141 4.135 0.000 0.044 2.577 0.010 0.051 2.871 0.004
Type (abc') 0.023 Complementary mediation 0.012 Complementary mediation 0.01 Complementary mediation
M
o
d
e
l
Models 1 & 2 Mediator: Perceived Learning Mediator: Practical Approaches Mediator:Access to Resources
Dependent
Variable=
Desirability Model assessments (1) Model assessments (2) Model assessments (3)
Variables B(1) t (1) Sig. (1) F (sig), R, R sq, Rsq adj. B(2) t (2) Sig.(2) F (sig), R, R sq, R sq adj. B(3) t (3) Sig. (3) F (sig), R, R sq, R sq adj.
1 (Constant) 2.930 13.404 0.000 F=35.607(p=0.000) 2.930 13.359 0.000 F=35.369(p=0.000) 2.930 13.344 0.000 F=35.289(p=0.000)
LocusOfCont(c) 0.303 5.967 0.000 R=0.271, Rsq=0.074 0.303 5.947 0.000 R=0.271, Rsq=0.074 0.303 5.940 0.000 R=0.271, Rsq=0.074
Rsq adj=0.072 Rsq adj=0.072 Rsq adj=0.072
2 (Constant) 2.113 8.636 0.000 F=40.143 (p=0.000) 2.604 11.467 0.000 F=28.200(p=0.000) 2.719 11.321 0.000 F=20.038(p=0.000)
LocusOfCont(c') 0.176 3.354 0.001 FΔ (41.463, p=0.000) 0.269 5.329 0.000 FΔ (19.556, p=0.000) 0.283 5.472 0.000 FΔ (4.507, p=0.034)
Mediator (b) 0.323 6.439 0.000 R=0.390, Rsq=0.152 0.153 4.422 0.000 R=0.336, Rsq=0.113 0.092 2.123 0.034 R= 0.288, Rsq=0.083
Rsq adj=0.148 Rsq adj=0.109 Rsq adj=0.079
3 (Constant) 2.526 12.818 0.000 F=73.701 (p=0.000) 2.124 7.222 0.000 F=10.471(p=0.001) 2.292 9.565 0.000 F=15.540(p=0.000)
LocusOfCont(a) 0.393 8.585 0.000 R=0.376, Rsq=0.141 0.221 3.236 0.001 R=0.152, Rsq=0.023 0.220 3.942 0.000 R=0.184,Rsq=0.034
Rsq adj=0.139 Rsq adj=0.021 Rsq adj=0.032
Sobel test (ab) B1 Z Sig. B1 Z Sig. B3 Z Sig.
Mediation 0.120 3.846 0.000 0.032 2.475 0.013 0.021 1.985 0.049
Type (abc') 0.022 Complementary mediation 0.009 Complementary mediation 0.01 Complementary mediation
M
o
d
e
l
308
Appendix 9.1521- EE Mediating the Effect of Need for Achievement on Feasibility
Appendix 9.1622- EE Mediating the Effect of Need for Achievement on Desirability
Appendix 9.1723- EE Mediating the Effect of Prior Entrepreneurial Exposure on Feasibility
Models 1 & 2 Mediator: Perceived Learning Mediator: Practical Approaches Mediator:Access to Resources
Dependent
Variable=
Feasibility Model assessments (1) Model assessments (2) Model assessments (3)
Variables B(1) t (1) Sig. (1) F (sig), R, R sq, Rsq adj. B(2) t (2) Sig.(2) F (sig), R, R sq, R sq adj. B(3) t (3) Sig. (3) F (sig), R, R sq, R sq adj.
1 (Constant) 2.446 11.106 0.000 F=23.319(p=0.000) 2.446 11.081 0.000 F=23.214(p=0.000) 2.446 11.056 0.000 F=23.109(p=0.000)
AchievementN(c) 0.246 4.829 0.000 R=0.223, Rsq=0.050 0.246 4.818 0.000 R=0.223, Rsq=0.050 0.246 4.807 0.000 R=0.223, Rsq=0.050
Rsq adj=0.048 Rsq adj=0.048 Rsq adj=0.048
2 (Constant) 1.423 5.666 0.000 F=39.657 (p=0.000) 1.995 8.813 0.000 F=29.595 (p=0.000) 1.913 7.993 0.000 F=25.194(p=0.000)
AchievementN(c') 0.106 2.056 0.040 FΔ (53.256, p=0.000) 0.198 3.975 0.000 FΔ (34.235, p=0.000) 0.196 3.874 0.000 FΔ (25.969, p=0.000)
Mediator (b) 0.385 7.298 0.000 R=0.389, Rsq=0.152 0.213 5.851 0.000 R=0.344, Rsq=0.118 0.231 5.096 0.000 R= 0.321, Rsq=0.103
Rsq adj=0.148 Rsq adj=0.114 Rsq adj=0.099
3 (Constant) 2.655 14.195 0.000 F=69.933 (p=0.000) 2.113 7.616 0.000 F=12.102 (p=0.001) 2.311 10.207 0.000 F=16.790(p=0.000)
AchievementN(a) 0.361 8.363 0.000 R=0.369, Rsq=0.136 0.223 3.479 0.001 R=0.163, Rsq=0.027 0.214 4.098 0.000 R=0.192,Rsq=0.037
Rsq adj=0.134 Rsq adj=0.024 Rsq adj=0.034
Sobel test (ab) B1 Z Sig. B1 Z Sig. B3 Z Sig.
Mediation 0.123 3.980 0.000 0.045 2.783 0.005 0.049 2.929 0.003
Type (abc') 0.015 Complementary mediation 0.009 Complementary mediation 0.01 Complementary mediation
M
o
d
e
l
Models 1 & 2 Mediator: Perceived Learning Mediator: Practical Approaches Mediator:Access to Resources
Dependent
Variable=
Desirability Model assessments (1) Model assessments (2) Model assessments (3)
Variables B(1) t (1) Sig. (1) F (sig), R, R sq, Rsq adj. B(2) t (2) Sig.(2) F (sig), R, R sq, R sq adj. B(3) t (3) Sig. (3) F (sig), R, R sq, R sq adj.
1 (Constant) 2.914 14.182 0.000 F=41.430(p=0.000) 2.914 14.151 0.000 F=41.244(p=0.000) 2.914 14.119 0.000 F=41.058(p=0.000)
AchievementN(c) 0.306 6.437 0.000 R=0.292, Rsq=0.085 0.306 6.422 0.000 R=0.292, Rsq=0.085 0.306 6.408 0.000 R=0.292, Rsq=0.085
Rsq adj=0.083 Rsq adj=0.083 Rsq adj=0.083
2 (Constant) 2.080 8.754 0.000 F=42.286 (p=0.000) 2.600 12.104 0.000 F=30.666 (p=0.000) 2.715 11.868 0.000 F=22.661(p=0.000)
AchievementN(c') 0.192 3.920 0.000 FΔ (39.552, p=0.000) 0.272 5.759 0.000 FΔ (18.462, p=0.000) 0.287 5.928 0.000 FΔ (3.986, p=0.046)
Mediator (b) 0.314 6.289 0.000 R=0.400, Rsq=0.160 0.149 4.297 0.000 R=0.349, Rsq=0.122 0.086 1.997 0.046 R= 0.306, Rsq=0.093
Rsq adj=0.156 Rsq adj=0.118 Rsq adj=0.089
3 (Constant) 2.655 14.195 0.000 F=69.933 (p=0.000) 2.113 7.616 0.000 F=12.102 (p=0.001) 2.311 10.207 0.000 F=16.790(p=0.000)
AchievementN(a) 0.361 8.363 0.000 R=0.369, Rsq=0.136 0.223 3.479 0.001 R=0.163, Rsq=0.027 0.214 4.098 0.000 R=0.192,Rsq=0.037
Rsq adj=0.134 Rsq adj=0.024 Rsq adj=0.034
Sobel test (ab) B1 Z Sig. B1 Z Sig. B3 Z Sig.
Mediation 0.103 3.748 0.000 0.032 2.634 0.008 0.017 1.996 0.047
Type (abc') 0.022 Complementary mediation 0.009 Complementary mediation 0.01 Complementary mediation
M
o
d
e
l
Models 1 & 2 Mediator: Perceived Learning Mediator: Practical Approaches Mediator:Access to Resources
Dependent
Variable=
Feasibility Model assessments (1) Model assessments (2) Model assessments (3)
Variables B(1) t (1) Sig. (1) F (sig), R, R sq, Rsq adj. B(2) t (2) Sig.(2) F (sig), R, R sq, R sq adj. B(3) t (3) Sig. (3) F (sig), R, R sq, R sq adj.
1 (Constant) 2.876 25.579 0.000 F=34.427(p=0.000) 2.876 25.493 0.000 F=34.196(p=0.000) 2.876 25.493 0.000 F=34.196(p=0.000)
PriorEntExp(c) 0.404 5.867 0.000 R=0.267, Rsq=0.072 0.404 5.848 0.000 R=0.267, Rsq=0.072 0.404 5.848 0.000 R=0.267, Rsq=0.072
Rsq adj=0.069 Rsq adj=0.069 Rsq adj=0.069
2 (Constant) 1.353 6.269 0.000 F=52.324 (p=0.000) 2.263 15.378 0.000 F=37.553 (p=0.000) 2.151 12.592 0.000 F=33.469(p=0.000)
PriorEntExp(c') 0.329 5.064 0.000 FΔ (65.271, p=0.000) 0.367 5.500 0.000 FΔ (38.055, p=0.000) 0.369 5.491 0.000 FΔ (30.472, p=0.000)
Mediator (b) 0.391 8.079 0.000 R=0.436, Rsq=0.190 0.219 6.169 0.000 R=0.381, Rsq=0.145 0.242 5.520 0.000 R= 0.362, Rsq=0.131
Rsq adj=0.186 Rsq adj=0.141 Rsq adj=0.127
3 (Constant) 3.900 38.119 0.000 F=9.312 (p=0.002) 2.801 19.449 0.000 F=3.755 (p=0.050) 3.001 25.444 0.000 F=4.026 (p=0.045)
PriorEntExp(a) 0.191 3.052 0.002 R=0.142, Rsq=0.020 0.171 1.938 0.050 R=0.091, Rsq=0.008 0.145 2.007 0.045 R=0.094,Rsq=0.009
Rsq adj=0.018 Rsq adj=0.006 Rsq adj=0.007
Sobel test (ab) B1 Z Sig. B1 Z Sig. B3 Z Sig.
Mediation 0.073 2.877 0.004 0.036 1.998 0.049 0.034 1.988 0.047
Type (abc') 0.025 Complementary mediation 0.014 Complementary mediation 0.01 Complementary mediation
M
o
d
e
l
309
Appendix 9.1824- EE Mediating the Effect of Prior Entrepreneurial Exposure on Desirability
Appendix 9.1925- GEM Data on EI and Gain on EI from EE
Compiled from: (Kelley et al., 2011; Kelley et al., 2012; Martínez et al., 2010)
Appendix 9.2026- GEM & World Bank Data on Entrepreneurship and Ease of Doing Business Rank
Compiled from: (Business, 2010; Kelley et al., 2011; Kelley et al., 2012; Martínez et al., 2010; World Bank, 2012)
Models 1 & 2 Mediator: Perceived Learning Mediator: Practical Approaches Mediator:Access to Resources
Dependent
Variable=
Desirability Model assessments (1) Model assessments (2) Model assessments (3)
Variables B(1) t (1) Sig. (1) F (sig), R, R sq, Rsq adj. B(2) t (2) Sig.(2) F (sig), R, R sq, R sq adj. B(3) t (3) Sig. (3) F (sig), R, R sq, R sq adj.
1 (Constant) 3.919 35.757 0.000 F=8.287(p=0.004) 3.919 35.638 0.000 F=8.231(p=0.004) 3.919 35.598 0.000 F=8.213(p=0.004)
PriorEntExp(c) 0.193 2.879 0.004 R=0.134, Rsq=0.018 0.193 2.869 0.004 R=0.134, Rsq=0.018 0.193 2.866 0.004 R=0.134, Rsq=0.018
Rsq adj=0.016 Rsq adj=0.016 Rsq adj=0.016
2 (Constant) 2.462 11.667 0.000 F=35.933 (p=0.000) 3.434 23.597 0.000 F=16.479 (p=0.000) 3.545 20.754 0.000 F=8.238(p=0.000)
PriorEntExp(c') 0.122 1.915 0.056 FΔ (62.447, p=0.000) 0.164 2.482 0.013 FΔ (24.299, p=0.000) 0.175 2.607 0.009 FΔ (8.132, p=0.005)
Mediator (b) 0.374 7.902 0.000 R=0.371, Rsq=0.138 0.173 4.929 0.000 R=0.262, Rsq=0.069 0.125 2.852 0.005 R= 0.189, Rsq=0.036
Rsq adj=0.134 Rsq adj=0.065 Rsq adj=0.031
3 (Constant) 3.900 38.119 0.000 F=9.312 (p=0.002) 2.801 19.449 0.000 F=3.755 (p=0.050) 3.001 25.444 0.000 F=4.026 (p=0.045)
PriorEntExp(a) 0.191 3.052 0.002 R=0.142, Rsq=0.020 0.171 1.938 0.050 R=0.091, Rsq=0.008 0.145 2.007 0.045 R=0.094,Rsq=0.009
Rsq adj=0.018 Rsq adj=0.006 Rsq adj=0.007
Sobel test (ab) B1 Z Sig. B1 Z Sig. B3 Z Sig.
Mediation 0.068 2.814 0.005 0.028 1.998 0.048 0.018 1.992 0.046
Type (abc') Indirect only mediation 0.005 complementary mediation 0.003 Complementary mediation
M
o
d
e
l
Sample Results Reflect % of 18-
64 year old Responses
EI training Gain
Ratio(GEM special
EE Report)
2010 2012 2010 2012 2010 2012 2010 2012 2010 2012 2010 2012 2010 2012 2010
Factor Driven economies
Zambia (N=2039, N=2157) 81 78 78 84 13 17 70 67 72 79 73 72 67 55
Ghana(N=2447,N=2222) 76 79 75 86 10 18 91 84 91 91 79 82 69 60
Group Average(unweighted) 62 63 72 71 29 28 75 76 81 80 65 68 43 48 2.2
Efficiency Driven Economies
South Africa (N=3279,N=2928) 41 35 44 39 29 31 78 74 78 74 79 73 17 12
China (N=3677,N=3684) 36 32 42 38 32 36 70 72 77 76 77 80 27 20
Group Average(unweighted) 43 41 56 52 32 32 73 70 70 69 63 60 23 26 1.9
Innovation Driven Economies
United Kingdom(N=3000,N=2000) 29 33 52 47 30 36 51 50 77 77 52 47 5 10
United States(N=4000,N=5542) 35 43 60 56 27 32 65 0 76 0 68 0 8 13
Netherlands(N=3502,N=3501) 45 34 46 42 24 30 85 79 69 65 61 58 6 9
Group Average(unweighted) 33 31 44 36 33 39 59 53 70 68 56 56 8 10 1.9
Entrepreneurial
Intention (EI)
Perceived
Opportunities
Perceived
Capabilities
Fear of
Failure
Enpreneurship
as a good
career choice
High Status to
successful
entrepreneurs
Media Attention
to
Entrepreneurship
Sample Results Reflect % of 18-
64 year olds' Responses
%trained
nascent &
new business
entrepreneurs
% of trained
individuals in
the population
TEA
training
Gain
index
2010 2012 2010 2012 2010 2012 2010 2012 2010 2012 2010 2012 2010 2012 2010 2012
Factor Driven economies
Zambia (N=2039, N=2157) 17 27 17 15 33 41 10 4 24 20 32 32 41 46 76 94
Ghana(N=2447,N=2222) 11 15 25 23 34 37 36 38 26 16 37 28 35 51 67 64
Average(unweighted) 12 12 12 13 23 24 13 11 13 13 34 35 38 42 32 21.2 1.5
Efficiency Driven Economies
South Africa (N=3279,N=2928) 5 4 4 3 9 7 2 2 5 5 36 32 31 40 34 39
China (N=3677,N=3684) 5 5 10 7 14 13 14 12 6 4 42 37 34 39 79 91
Average(unweighted) 7 8 5 6 12 13 8 8 4 5 31 28 42 46 33.6 19.8 1.8
Innovation Driven Economies
United Kingdom(N=3000,N=2000) 3 5 3 4 6 9 6 6 2 2 11 18 43 43 4 7
United States(N=4000,N=5542) 5 9 3 4 8 13 8 9 4 4 28 21 51 59 5 4
Netherlands(N=3502,N=3501) 4 4 3 6 7 10 9 9 1 2 8 8 64 66 30 31
Average(unweighted) 3 4 3 3 6 7 7 7 2 3 20 18 54 51 40.9 23.4 2.1
Improvement
Driven
Opportunity
(% of TEA)
Doing Business
Global Ranking
(out of 183
countries)*
2010 special Report on EE & Training
* easy of starting a business, paying taxes, trading across borders, registering property, dealing with construction permits, getting credit, closing a business, enforcing contracts & protecting investors
Nascent
Ent.ship Rate
New Business
ownership
Rate (≤3.5 yrs)
Early-stage
Ent.Ship
Activity (TEA)
Established
Business
Ownership Rate
(>3.5yrs)
Discontinued
businesses
Necessity
Driven(% of
TEA)
310
Appendix 10.127- List of Empirical Studies Reviewed on Determinants of EI and Outcomes
Key Empirical Studies Pertinent to Entrepreneurship Education, Institutions and Personality's Effects on Intention and Outcomes: 2002-2014
# Authors Approach Focus of Study Analysed Sample Findings
1 Altinay et al., 2012
Quantitative cross-sectional
The influence of family tradition and psychological traits on entrepreneurial intention (EI)
205 university students In hospitality and tourism studies in UK
Family tradition in entrepreneurship and innovativeness positively influence EI. However, risk taking propensity, tolerance for ambiguity, and locus of control have no significant influence on EI.
2 Aouni and Pirnay, 2009
Longitudinal quantitative
Workshops and conference based presentations from successful entrepreneurs (role models) aimed at young people (including college and university students)
668 youths in Belgium
Those with initial low interest in entrepreneurship reported positive change on ambition (intention). However, no impact on feasibility to start a business. Those with initial high interest in entrepreneurship reported negative change in ambition and no impact on feasibility of business start-up.
3 Bae et al., 2014
Meta-analyses quantitative
The relationship between entrepreneurship education (EE) and entrepreneurial intention (EI).
73 studies with a total sample size of 37285.
Significant but small correlation between EE and EI (r=0.143). This correlation was greater than that of general business education and EI. However, controlling for pre-education EI, the relationship between EE and post-education EI was not significant. Future studies can extend knowledge of effects of EE on EI by investigating mediation effects. In addition, future studies could consider selection bias influences.
4 Barakat et al., 2010
Longitudinal quantitative
Perceived feasibility before and after short (4 days) intensive EE programme for post-graduates with mean age 28.9 with no or little prior entrepreneurial exposure
192 University of Cambridge pre-course and post-course questionnaire and 6 months follow-up questionnaire
After programme, students showed higher perception of feasibility and the positive effect was sustained 6 months after the programme. Natural science students scored higher than social science students. Men scored higher than women. British students scored higher than overseas students.
5 BarNir et al., 2011
Quantitative cross-sectional
Effects of role models and self-efficacy on forming career intentions and whether the effects vary by gender
393 undergraduate students (180 men, 213 women) at a public university in USA comprising freshmen, seniors and graduate students in core business course with 25% respondents from other fields.
A moderated mediation relationship such that for women role models had stronger influence on self-efficacy which in turn influenced entrepreneurial career intentions
311
# Authors Approach Focus of Study Analysed Sample Findings
6 Birdthistle, 2008
Quantitative cross-sectional
Survey of intentions, personality factors using the big five factor model of personality traits plus locus of control, background factors and obstacles to nascence
248 students from 5 universities in Ireland
Personality traits and perceptions of obstacles (complicated legal processes, economic down-turn, lack of debt capital and lack of entrepreneurial skills) influenced intentions.
7 Bowen and De Clercq, 2007
Quantitative-secondary data
Assessing institutional context's influence on the allocation of entrepreneurial effort in a country.
40 countries' macro-economic data from 2002 -2004.
Increased financial capital and educational capital targeted at entrepreneurship and reduced corruption among a country's economic actors increases entrepreneurial activity including high growth entrepreneurial activity.
8 Byabashaija and Katono, 2011
Intention before and after the module but with no control group
The impact of university entrepreneurship education on the intention to start a business in Uganda
167 undergraduate students in Uganda. Analyses included tests of significance of changes in the attitudes and intentions of students after the entrepreneurship compulsory module, the mediating role of attitudes and moderating role of employment expectations.
The results show a statistically insignificant decrease in intention and small but significant changes in attitudes (feasibility, desirability and entrepreneurial self-efficacy) and a significant mediating role of feasibility and desirability (these attitudes also mediated subjective norms) but a non-significant moderating role of employment expectations.
9 Carr and Sequeira, 2007
Quantitative cross-sectional
Direct and indirect effect of prior family business exposure on intention and attitudes
308 respondents comprising nascent entrepreneurs, employees, unemployed and a few students in the USA.
Significant direct and indirect effect of prior family business exposure on EI through attitudes.
312
# Authors Approach Focus of Study Analysed Sample Findings
10 Collins et al., 2004
Quantitative cross-sectional
Assessing factors affecting entrepreneurial intentions (EI) for first year students
1194 fresher undergraduate students in three universities in Leicestershire, UK
Students enter university with some level of EI. Influences include family role models and prior experiences. They expect to start own businesses after gaining experience within 10 years after graduation.
11 Davey et al., 2011
Quantitative cross-sectional
Identify the differences between African and European students with regard to their entrepreneurial intentions (EI), attitudes towards entrepreneurship, role models and entrepreneurial experience
1055 first year university students from one university in Germany, Finland, Ireland, Portugal, South Africa, Uganda and Kenya
Students from developing/emerging economies in Africa have higher EI than their industrialised European counterparts. Motivations for choice of career were similar.
12 De Clercq et al., 2011
Quantitative Influence of individual level resources (financial, human and social capital) on new business activity and the cross-level moderating effect of formal institutions (financial and education systems) and informal institutions (trust and cultural values of hierarchy and conservatism)
181,450 observations from 32 developed economies (including UK) and emerging economies (including South Africa) based on 2003 to 2007 GEM data on nascent entrepreneurship, financial, human and social capital, GEM national experts assessment of formal institutions, the world values survey (WVS) and Schwartz's cultural value framework
Financial, human and social capital increases new business activity (preparing to start or started but less than 42 months in business). Entrepreneurs with abundant financial resources are not affected by institutional context when starting. However, in countries with financial and education system less oriented to new business creation, the possession of skills, knowledge and experience (human capital) as well as direct exposure to entrepreneurial role models (social capital) become less instrumental for the prevalence of new business activity.
313
# Authors Approach Focus of Study Analysed Sample Findings
13 do Paco et al., 2013
Quantitative cross-sectional
Entrepreneurial intentions (EI): is education enough? This study seeks to compare the psychological attributes and behaviours associated with entrepreneurship, as well as EI among girls attending a business school and boys attending a sports school.
232 students in Portugal
It was expected that the scores recorded for EI would be higher at the girls’ business school, where entrepreneurship education (EE) is deeply incorporated into the curriculum, but the results showed that, despite their not receiving any kind of EE, the boys at the neighbouring sports school tended to have higher EI, which suggests that there are other factors influencing EI.
14 Dohse and Walter, 2012
Quantitative cross-sectional
The role of the individual and regional knowledge context in formation of entrepreneurial intention
1816 male students in computer science, electrical engineering and business in Germany universities
At individual level, role models facilitating transfer of tacit knowledge and the expectation that strong ties will provide know-who and know-how positively impact intention. Need for achievement, risk taking propensity, need for independence, opportunity perception also significantly influence EI. At regional level, high regional start-up rate in knowledge-based industries and high growth rate of regional knowledge influence intention. Unemployment level among highly qualified had no significant influence.
15 Engle et al., 2011
Quantitative cross-sectional
Institutions and entrepreneurial intent (EI): a cross country study
477 university business students from Russia, USA and Germany
Minor support for influence of formal institutions on EI based on World Bank's Doing Business ranking. Greater impact on EI from informal institutions of need, social norms and parental experience.
16 Ertuna and Gurel, 2011
Quantitative cross-sectional
Moderating role of number of years in university education on relationship between traits, background and intentions
917 first year and final year business and engineering students from five universities in Turkey.
Risk taking propensity (not innovativeness or locus of control) interacts with number of years in university (education) to increase odds of stating intention.
314
# Authors Approach Focus of Study Analysed Sample Findings
17 Fairlie and Holleran, 2011
Quantitative longitudinal 2003-2005
Influence of entrepreneurial personality traits on benefits from entrepreneurship training measured through rate of business ownership
Used survey results from the Department of Labour for Growing America Through Enterprise (GATE) project that enrolled people for free training and coaching in business creation and management. Survey was done at three intervals, wave 1 (6 months, 2597 sample), wave 2 (18 months, 2265 sample) and wave 3 (60 months, 1821 sample)
Individuals with risk tolerance had higher benefit from entrepreneurship training because they had higher business creation and ownership rate. Inconclusive results for innovativeness and autonomy.
18 Falck et al., 2012
Quantitative
Identity and entrepreneurship: do school peers shape entrepreneurial intentions (EI)?
The study was based on Programme for International Student Assessment (PISA) 2006 data with a restricted sample of 52,783 for final year students in secondary school reporting EI at the age of 15 for OECD countries. The study also uses data from the longitudinal British Cohort Study (BCS) since 1970.
Based on the BCS, individuals who at age 16 expressed EI were more likely to become entrepreneurs by age 34. Based on PISA data, having an entrepreneurial peer group (school peers with at least one parent who is an entrepreneur) and having entrepreneur parents has a positive effect on EI. Thus, entrepreneurial identity results from an individual's socialisation. The strength of peer effect in a country is moderated by prevailing values of individualism/collectivism.
315
# Authors Approach Focus of Study Analysed Sample Findings
19 Fayolle and Gailly, 2009
Quantitative longitudinal
Assessing the impact of entrepreneurship education programmes (EEP): a new methodology and three experiments from French engineering schools
Engineering students from three universities in France, Grenoble (20 students, one day programme), Limoges EEP (43 students, seven months programme) and Lyon EEP (144 students, three days programme)
Students with previous exposure in entrepreneurship (closer role models or prior actual experience) showed little change while those without showed significant change in intentions after the programme. Those in a longer EEP also showed higher intentions.
20 Fitzsimmons and Douglas, 2011
Quantitative cross-sectional
Interaction between feasibility and desirability in the formation of entrepreneurial intention (EI)
414 MBA students answered a questionnaire at the start of an entrepreneurship module in Australia (46), China (39), India (204) and Thailand (125)
EI was very high or sufficiently high with the following combinations of feasibility and desirability: a) high/high (natural entrepreneur-very high EI), b) high/low (accidental entrepreneur-sufficiently high EI), c) low/high (inevitable entrepreneur-sufficiently high EI), and d) low/low ( non-entrepreneurs, low EI)
21 Frank et al., 2007
Quantitative longitudinal
The significance of personality (need for achievement, risk taking propensity, locus of control) in business start-up intentions, start-up realisation and business success
417 (18 year olds), 777 (university students), 314 (business founders), and 1169 (successful entrepreneurs) over three years in Austria.
Personality traits are significant at intentions stage but reduce during nascence and finally become negligible for success (survival/growth) as environment/resources (human, social and financial capital) and process (managerial skills) gain significance.
22 Fretschner and Weber, 2013
Quantitative longitudinal
Impact of entrepreneurship awareness education- assessment based on theory of planned behaviour
75 (pre-test) and 62 (post-test) business students in the University of Munich, Germany
Attitude to entrepreneurship significantly impacts EI in both pre-test and post-test assessment. However, in an awareness setting, perceived behavioural control does not significantly impact EI in the post-EE assessment.
316
# Authors Approach Focus of Study Analysed Sample Findings
23 Galloway et al., 2005
Quantitative cross-sectional
Attitude to entrepreneurship and perception of the economic environment by university students
451 students who just completed an entrepreneurship module in 2003 in 4 Scottish universities, Herriot-Watt University, Napier University, University of Strathclyde and University of Paisley
Most students in the short term expect to work in new and small firms and that skills developed by entrepreneurship education are applicable to both wage employment and entrepreneurship. In the long term, 5-10 years, students expect to start and run their own businesses.
24 Gaspar, 2009
Quantitative Effect on venture creation decision and performance of support from venture capitalists (VCs) and business incubation centres (BICs)
119 start-ups, 15 VCs, 18 BICs in Portugal
Support from VCs and BICs positively influence decision to create new business, reduced start-up mortality rate and improved performance. Human capital (individual's knowledge and experience) and internal locus of control also have positive influence.
25 Gasse and Tremblay, 2011
Quantitative cross-sectional
Compare the intentions and nascence of university students in cross-cultural and socio-economic contexts
2053 mostly undergraduate students: Canada 341, Tunisia 209, France 312, Romania 410, UK 239, Colombia 102 and Germany 440.
Perception of feasibility and desirability as well as personality traits predict intentions across countries. Nascence was also found to be high among less developed countries.
26 Giacomin et al., 2011
Quantitative cross-sectional
Differences in entrepreneurial intentions between countries and perceived barriers and motivations
2093 students from five universities in five countries (India, China, Spain, Belgium, USA)
Intentions differ between countries but students are motivated and or/discouraged by similar variables. However, the levels of sensitivity to each motivator or barrier differ by country.
317
# Authors Approach Focus of Study Analysed Sample Findings
27 Gibcus et al., 2012 for the European Commission
Quantitative cross-sectional
Effects and impact of EE on entrepreneurial attitudes, skills, intention, actual start-up and employability for higher education alumni
1139 EE alumni and 1443 control group from 9 universities in 9 European countries i.e. UK, Sweden, Finland, Netherlands, Spain, Germany, Croatia, Austria and Ireland
EE has positive effect on entrepreneurial attitudes (initiative, self-efficacy, risk taking propensity, achievement need and structural behaviour), skills (adaptability, creativity, analysis, networking, motivation) and knowledge (role and mechanics of entrepreneurship and entrepreneurs) but not self-efficacy when EE group is compared to control group. EE group had higher EI and preference for self-employment. Independence, realising business opportunity, freedom of choice of time/place of work are motivations for both groups though the EE group more often (68% vs 61%) mentioned realising a business opportunity (pull factors) and less often mentioned lack of attractive job opportunities and avoiding uncertainty of being an employee than the control group (push factors). Among those with preference for organisational employment, control group scores higher than EE group on security, stability motivations such as regular fixed income, social security protection, avoiding dealing with red-tape and problems with authorities. Males have higher EI than females. Preference for self-employment decreases with age. EE group generally found employment sooner after graduation (78% vs 59%). EE group earned more money and were more creative in their current job. EE group had higher proportions for those who became self-employed (16% vs 10%), entrepreneurs (8% to 3%), liberal professions and freelancers (8% vs 7%). EE group started a business within 0.7 years after graduation while control group started 2.8 years later. EE group had higher actual innovation and turnover as well as more ambitious growth forecasts for their businesses than the control group. Among entrepreneurs, over a period of 10 years, the EE group had more serial entrepreneurs.
318
# Authors Approach Focus of Study Analysed Sample Findings
28 Guerrero et al., 2008
Quantitative cross-sectional
The influence of desirability and feasibility on entrepreneurial intentions
719 university students (from 2nd to 5th Year) in two universities in Spain. 279 in entrepreneurship related majors and the rest as controls in various disciplines.
Perception of desirability and feasibility on intention was not significant when tested with all university students even for those with entrepreneurship education (EE). Significant only with respective sub samples. Demographic variables of role models and prior experience as well as EE had a positive influence on attitudes but not on feasibility.
29 Gurel et al., 2010
Quantitative cross-sectional
Moderating role of number of years in university education on relationship between traits, background and intentions
First year and final year tourism students: UK (206) and Turkey (203)
No moderating effect for UK and Turkey samples (innovativeness and risk taking propensity on their own were associated with intentions)
30 Haase et al., 2011
Quantitative cross-sectional
Differences in entrepreneurial intentions between developing and developed countries
2353 students from one university in Namibia and two universities in Germany
Developing country respondents have higher intentions and more self-employed friends and relatives.
31 Henley, 2007 Quantitative longitudinal
Entrepreneurial aspiration and transition into self-employment- evidence from UK
Used the British Household Panel Survey (BHPS) data from 1998 to 2002 with a sample of 13751
Successful transition from intentions to actual entrepreneurship is more likely if intentions are well formed in advance. Time span between intentions and actual entrepreneurship is subject to wide variations (from months to years). The highly educated and younger are more likely to aspire to start a new venture. The younger may aspire to start but lack resources, skills and experience. Gender, ethnicity, prior work and/or entrepreneurial experience, education and family self-employment background also explain transition to actual self-employment.
319
# Authors Approach Focus of Study Analysed Sample Findings
32 Henry et al., 2004
Qualitative longitudinal
Quantitative and qualitative impact of training in new business creation over three years in Ireland
35 participants on a part-time training scheme with either a Diploma or degree with business idea; control group with 48 aspiring entrepreneurs with a business idea not on the training programme due to limited places; 38 comparator group on a different 6 months training programme facing imminent redundancy.
Training increased perception of entrepreneurial capability, access to support networks, and the treatment group had more self-employed people and generated more businesses and new jobs.
33 Kautonen et al., 2013
Quantitative longitudinal 2011-2012
Robustness of the theory of planned behaviour in predicting entrepreneurial intention and actions
969 adults in Austria and Finland (wave 1) with a decline from 58% to 8% (Austria) and 73% to 23 % (Finland) in terms of response rate in Wave 2.
Subjective norms, attitudes and perceived behavioural control (PBC) explain 59% variation in intention. Intention and PBC explain 31% of subsequent behaviour.
34 lakovleva et al., 2011
Quantitative cross-sectional
Differences in applicability of the theory of planned behaviour (TPB) in entrepreneurial intention (EI) between efficiency-driven and innovation-driven economies
2225 students from 8 developed countries (Australia, France, Canada, Czech Republic, Norway, Spain, Germany, and Netherlands) and 5 developing countries (Mexico, Brazil, Romania, Russia and Ukraine)
Respondents from efficiency-driven economies have higher EI than those from innovation-driven economies because of higher attitudes, social norms and perceived behavioural control. The TPB is fully replicable in efficiency-driven and innovation-driven economies.
320
# Authors Approach Focus of Study Analysed Sample Findings
35 Kristiansen and Indarti, 2004
Quantitative cross-sectional
Assessing factors affecting entrepreneurial intentions in different economic and cultural contexts
University students in Indonesia (130) and Norway (121)
The developing country had higher intentions due to higher need for achievement, self-efficacy and positive evaluation of access to capital, social networks and information about how to start a business. It is easier to start a business in the informal sector. In a developed country with low unemployment rate, most of the entrepreneurial and innovative processes take place in large organisations and individual business start-up has low social status.
36 Levenburg et al., 2006
Quantitative cross-sectional
Interdisciplinary dimension of entrepreneurial intentions
728 students at one university in USA (Grand Valley State University)
No difference between majors in intentions. However, desire for entrepreneurship education is more in non-business students.
37 Lim et al., 2010
Quantitative Institutional elements' effects on venture creation decision (VCD) mediated by entrepreneurial cognition/expert scripts
757 entrepreneurs and non-entrepreneurs from USA, Canada, UK, Australia, Germany, France, Italy and Japan as well as World Bank database on financial structure and development.
Results show that institutional elements (property rights, simplicity of start-up formalities, number of years in education, financial system and perception of corruption) affect venture arrangement (knowledge about what is needed to start a business), willingness and ability which in turn impact VCD.
38 Liñán et al., 2011
Quantitative cross-sectional
Closer valuation (subjective norms) and social valuation (societal admiration) of entrepreneurship and their effects on intentions in different regions.
549 final year students in business and economics classes from two different regions of Spain
Closer valuation of entrepreneurship seems to exert a stronger influence on personal attitude (desirability) while social valuation affects behaviour control (feasibility) perceptions. The effects are regionally different. Demographic and background factors are mediated by desirability and feasibility.
39 Liñán et al., 2011
Quantitative cross-sectional
Which factors are more important in EI among attitudes, situational factors and knowledge of contextual entrepreneurial support?
354 final year undergraduate business and economics students in Spain
Results confirm that perceived feasibility and desirability are the main factors explaining EI. Therefore, it may be reasonably argued that EE should consider stimulating entrepreneurship by developing perceptions of feasibility and desirability.
321
# Authors Approach Focus of Study Analysed Sample Findings
40 Liñán, 2008 Quantitative cross-sectional
Effect of perceptions of closer and social valuation of entrepreneurship and perception of entrepreneurial skills on intentions
249 final year business and economics students from one Spanish university.
Closer valuation of entrepreneurship and perception of entrepreneurial skills have a strong effect on intentions though skills have a stronger effect. Wider valuation was influencing EI through entrepreneurial skills.
41 Liñán and Chen, 2009
Quantitative cross-sectional
Development and cross-cultural application of a specific instrument to measure entrepreneurial intention (EI)
387 business and economics final year students in Spain from three universities and 132 business, engineering, health and life science students participating in a business plan competition in Taiwan
Personal attitude (PA) and perceived behavioural control (PBC) have a direct effect on EI whereas subjective norm (SN) has no direct effect on EI but has an indirect effect by influencing PA and PBC. These findings are in line with previous studies that show a weak direct link between SN and EI. Demographic and human capital variables have relatively a small impact on the antecedents of EI.
42 Luthje and Franke, 2003
Quantitative cross-sectional
Effects of traits and contextual perceived barriers and support factors on entrepreneurial intent
512 MIT engineering students answered a questionnaire which had personality traits, attitude to entrepreneurship and contextual start-up barriers and support factors
Personality traits had an indirect relationship with intentions mediated by attitude while perceived barriers and perceived support had a direct effect on intentions. Attitude though had the strongest influence on intentions.
43 Luthje and Franke, 2004
Quantitative cross-sectional
Comparison of entrepreneurial intentions (EI) in different institutional and university contexts
1313 undergraduate students at Massachusetts Institute of Technology (MIT) in USA and two universities in Germany
Where personality factors are comparable, differences in EI are affected by contextual factors both in the macro environment (laws, access to finance, markets, social acceptability, etc.) and in the micro environment (university environment that fosters creativity, innovation, start-up skills, networking and other support).
322
# Authors Approach Focus of Study Analysed Sample Findings
44 Manolova et al., 2008
Quantitative cross-sectional
Validate an instrument for measuring country institutional profiles for the promotion of entrepreneurship
254 business students from three emerging economies: Bulgaria, Hungary and Latvia
The Busenitz et al. (2000) instrument was validated for use in emerging markets. The ranking of the three countries' results from this survey found support from GEM ''nascent entrepreneurship ranking'', World Bank development indicators and ''Doing Business ranking''
45 Marques et al., 2012
Quantitative cross-sectional
Impact of entrepreneurship education (EE), psychological and demographic factors in prediction of entrepreneurial intention (EI)
202 secondary school students in Portugal.
Attitude, subjective norms, perceived behavioural control positively influence EI. Need for recognition (positively) and tolerance for ambiguity (negatively) influence EI. EE does not have a significant influence on EI.
46 Martin et al., 2013
Meta-analyses quantitative
Examining impact of entrepreneurship education (EET) on entrepreneurship outcomes (nascence, start-up, performance) and the formation of human capital assets (knowledge, skills, and competences), positive perceptions (attitudes, desirability, feasibility, and self-efficacy) and intention.
42 studies with 42 independent samples with total sample size of 16657 individuals
Overall small effect size but significant relationship between EET and entrepreneurship-related human capital assets (r =0.217) and outcomes (r=0.159). But the relationship with outcomes is stronger for academic focused EET interventions (r=0.238) than for training focused EET interventions (r=0.151). Studies with less methodological rigor overstate the effect of EET. Significant results between EET and knowledge/skills (r=0.237); positive perception of entrepreneurship (r=0.109); and, intentions (r=0.137)
323
# Authors Approach Focus of Study Analysed Sample Findings
47 Martinez et al., 2010
Quantitative cross-sectional
Influence of entrepreneurship training on intentions and activity for the working age population (18-64 years old)
The GEM survey covered 38 countries (6 factor-driven economies including Egypt, 17 efficiency-driven economies including South Africa and 15 innovation-driven economies including the UK). Experts also rated the environment in each country.
Training increases awareness, self-efficacy and intentions but less influence on the fear of failure and opportunity recognition. Across the 38 countries, entrepreneurs are more likely to have received training in starting a business (33%) than the rest of the working age population (20%). Early stage entrepreneurial activity is significantly associated with past training in starting a business. Entrepreneurs who have received training tap into a wider variety of advisors on how to start and run a business. Proportion of trained individuals and nascent entrepreneurs is higher in innovation-driven economies. Training doubles intention but not activity in factor-driven economies due to challenging entrepreneurship environment. Gain from training in terms of increased activity is greater in innovation-driven economies due to facilitating factors. The conversion of trained individuals to entrepreneurs is higher in countries with low rate of training than in countries with higher rate of training.
48 Matlay, 2008 Qualitative 1997-2007
Entrepreneurship education (EE), intentions and actual start-up
64 students from 8 UK universities from business, computing, arts and engineering schools
EE improved self-evaluation of entrepreneurial skills, influenced intention and activity for all respondents over 10 years. 59 reported prior family entrepreneurial exposure influence.
49 Morris et al., 2013
Quantitative longitudinal
Development of competences through training and hands on practice in entrepreneurship education
40 students (15 from South Africa and 25 from USA) were first trained in entrepreneurship (morning sessions) and required to solve problems (afternoon sessions) for and with historically disadvantaged small business owners in South Africa over a period of six weeks.
Positive improvements were identified for all 40 students from the pre-test to the post-test results (six weeks) in all 13 entrepreneurial competences. However, t-tests indicate significant improvements in opportunity recognition, risk management/mitigation, tenacity/perseverance, creative problem solving, resource leveraging/bootstrapping, guerrilla skills, value creation/innovation, resilience, and networking skills.
324
# Authors Approach Focus of Study Analysed Sample Findings
50 Nabi et al., 2010
Quantitative Entrepreneurial intentions and awareness of support for start-up among university students in UK
Presents results from a data set of 8456 students from 10 universities in Yorkshire and Humberside in 2007/2008 and reflects back over similar iterations of the survey in 2003, 2004, 2005 and 2006
Decline in intentions from 2003 to 2008 among students (46% to 33%) with minorities showing higher intent. No discernible difference in intentions across years of study (1st to 3rd year students) which points to questionable impact of higher education. The majority of students (75%) were unaware of start-up support both within and outside the universities.
51 Nga and Shamugana-than, 2010
Quantitative cross-sectional
The effect of personality traits on social entrepreneurship intentions (SEI)
181 undergraduate Malaysian students
Personality traits (openness to experience, agreeableness and conscientiousness) have a positive influence on SEI.
52 Obschonka et al., 2010
Quantitative cross-sectional
Entrepreneurial intention (EI) as a developmental outcome
496 German scientists with an average age of 38
Personality (big five) and recalled early entrepreneurial activity in adolescence (early inventions, leadership and commercial activities) positively impacted EI.
53 Oosterbeek et al., 2011
Quantitative longitudinal
The impact of entrepreneurship education on entrepreneurship skills and motivation
189 treatment group and 220 control group (different campus but same college) at the beginning of academic year and 104 treatment group and 146 in the control group at the end of the Student Mini Company entrepreneurship programme in which students were grouped in ten to form a company under mentoring in a Netherlands College
The impact on students’ self-assessed skills is insignificant and the effect on intention is negative
325
# Authors Approach Focus of Study Analysed Sample Findings
54 Packham et al., 2010
Quantitative longitudinal
Impact of enterprise education (EE) and gender on entrepreneurial attitudes within European higher education for 18 to 24 year olds.
Students from France (112), Germany (66) and Poland (59) at beginning and end of a single entrepreneurship programme developed by Welsh Enterprise Institute (University of Glamorgan) taught in the three countries.
EE has positive effects on entrepreneurial attitudes (intentions) of French and Polish students but negative impact on German students. Males' intentions were higher in Germany and France than female intentions except in Poland were it was the opposite. German students said they were more interested in the educational experience of the course and not starting a business of their own. Low unemployment in Germany could have contributed to this.
55 Peterman and Kennedy, 2003
Quantitative longitudinal
Influencing students perception of entrepreneurship through entrepreneurship training
Pre-university secondary school students enrolled in Young Achievers of Australia (YAA) elective enterprise programme over 5 months answered a questionnaire in a pre-test- post-test setting with 117 participating students and 119 non- participating students
a) Prior exposure to entrepreneurship had a positive effect on students choosing to participate in the enterprise education programme b) After participation in the programme, there was increased desirability and perception of feasibility for venture creation than for those who did not participate in the programme
326
# Authors Approach Focus of Study Analysed Sample Findings
56 Prieto et al., 2010
Quantitative cross-sectional
Direct and mediating effects of individual factors (risk taking propensity and entrepreneurial self- efficacy) and environmental factors (family, self-employment background, social networks, legal system support, government support, and social norms) on the propensity for self-employment.
530 USA students at 3 universities and 378 Mexican students at 2 universities
Self-efficacy fully mediated the relationships. In hostile environments high-in-group collectivistic societies may also generate high levels of individualism. A strong formal institutions-individual nexus in the USA and a strong informal institutions-individual nexus in Mexico as well as a prominent impact of the individual in Mexico.
57 Rauch and Frese, 2007
Meta-analyses quantitative
Influence of personality traits matched to the tasks of entrepreneurship on the business creation decision and on success
62 studies with sample size of 13280 investigating business creation and 54 studies with sample size of 3975 dealing with business success
Traits matched to the task of managing a business produced higher effect sizes with business creation and success than traits that were not matched to managing an enterprise. These traits were need for achievement, generalised self-efficacy, innovativeness, stress tolerance, need for autonomy and proactive personality. Risk taking propensity and internal locus of control had low significance.
58 Robertson et al., 2003
Quantitative cross-sectional
Barriers to start-up and their effect on aspirant entrepreneurs
82 Leeds Metropolitan University students who stated intention to start within two years of graduation and compared to 224 Yorkshire and Humber regional aspirant entrepreneurs who were identified through Business Link.
Critical barriers cited by students were lack of finance, no available support, lack of skills, lack of confidence and lack of business ideas. The older regional aspirants had more confidence and had higher rates of start-ups. The authors attributed these differences to previous work experience.
327
# Authors Approach Focus of Study Analysed Sample Findings
59 Sanchez, 2013
Quantitative longitudinal 2011-2012
Pre-test and post-test impact of entrepreneurship education (EE) on entrepreneurial intention (EI) and competencies
347 EE participants and 363 non-participants among secondary school students in Spain.
Both t1 and t2 show that EI is related positively significantly to self-efficacy, pro-activeness and risk taking. For participants t2 means were significantly higher than t1 variables. However, non-participants' means show no significant difference. Mean values for participants were higher than those for non-participants.
60 Schlaegel and Koenig, 2014
Meta-analyses quantitative
A meta-analytical testing and integration of the theory of planned behaviour (TPB) and Shapero's entrepreneurial event (SEE) model.
98 studies providing 123 samples and n=114,007 individuals
Attitude to the behaviour (ATB), subjective norms (SN), entrepreneurial self-efficacy (ESE), and perceived behavioural control (PBC) have a combined predictive power on EI of R
2 28%. Propensity to act (insignificant),
perceived desirability and feasibility have a combined influence on EI of R
2 21%. Integrating the determinants,
ignoring propensity to act, produces a combined influence of R
2 31%; ATB (full), SN (partial), ESE (partial), and PBC
(full)'s influence on EI is significantly mediated by desirability and feasibility. Feasibility's influence on EI is partially mediated by desirability.
61 Segal et al., 2005
Quantitative cross-sectional
The role of tolerance for risk and perceptions of net desirability of self-employment and feasibility in entrepreneurial intention (EI)
114 undergraduate business students at Florida Gulf Coast University in USA
Tolerance for risk and perceptions of net desirability (between self-employment and working for others) and feasibility significantly predict EI.
62 Shinnar et al., 2012
Quantitative cross-sectional
Culture and gender differences in university students’ perception of barriers to entrepreneurship and formation of entrepreneurial intentions (EI)
761 students (147 Chinese, 285 American, and 329 Belgian) from one university in each country from first year to fifth year with 75.2% of students being from business and the rest from other disciplines.
Gender and culture do matter in the perceptions of lack of institutional support, competency and fear of failure and their relationship to EI but not consistently. Women perceive barriers to be more important.
328
# Authors Approach Focus of Study Analysed Sample Findings
63 Siu and Lo., 2013
Quantitative cross-sectional
Impact of individualism-collectivism orientation on the strength of perceived social norms on entrepreneurial intentions
204 MBA students from mainland China and Hong Kong
The predictive strength of social norms toward entrepreneurship is high for individuals with high level of interdependent self-construal (collectivist) and low for individuals with high independent self-construal (individualistic i.e. what others think is less influential)
64 Smith and Beasley, 2011
Qualitative Barriers and enablers that influenced recent graduates in the creative and digital industries to start their own businesses in Barnsley, South Yorkshire,UK
7 nascent graduate entrepreneurs who received a start-up grant from the Barnsley Business Mine in 2009-2010 were interviewed
Perceived barriers were lack of general business knowledge, contradictory advisory support from external agencies, lack of sector-specific mentors, lack of finance, and experience of familial entrepreneurship. Perceived enablers were co-mentoring from business partners, course content, creative and innovative ideas, increased linkages of external and internal support.
65 Solesvik et al., 2013
Quantitative cross-sectional
Effects of entrepreneurship education (EE) investment on entrepreneurial assets (alertness-scan, connect, evaluation; and, risk-taking-perception and propensity) and mind-set (intention)
Survey of 189 master and bachelor degrees students from three universities in Ukraine. EE participants were business students and control group were engineering students.
EE participants had higher intention than non-participants. EE participation interacted significantly with alertness to business opportunities (connection) in influencing intention. However, EE participants who accumulated the risk taking propensity asset reported lower intention. This meant that EE participants were more oriented to intention when they perceived less risk.
66 Souitaris et al., 2007
Quantitative longitudinal
Influence of entrepreneurship knowledge, inspiration, support services on entrepreneurial intentions
Pre-test-post-test quasi-experimental design for similar entrepreneurship modules among science and engineering students in two universities in London, UK, and Grenoble, France. 124 students took the module and 126 were in the control group.
Engineering students taking the entrepreneurship module increased their subjective norm and intention towards self-employment, whereas students in the control group did not though there was no nascence reported. Inspiration (and not perceived learning and knowledge from the module nor resource utilisation during the module) was the education's main benefit resulting in intentions.
329
# Authors Approach Focus of Study Analysed Sample Findings
67 Spencer and Gomez, 2004
Quantitative The role of country institutional profiles (normative, cognitive, and regulatory institutions) and their influence on basic, moderate and advanced forms of entrepreneurial activity
Institutional pillar ratings by 65 officers responsible for political, economic and commercial affairs assigned to US embassies in each of the 14 countries of study and similar officers from each country assigned to that country's embassy in USA. In addition, 1999 UN and World Bank employment, small businesses and GDP figures were used.
Favourable regulatory institutions positively associated with new stock exchange listings and negatively associated with self-employment; favourable cognitive institutions (entrepreneurial skills and abilities) positively affected small businesses and new listings; and favourable normative institutions marginally positively associated with high self-employment. Lower GDP per capita predicted high self-employment and high prevalence of small businesses.
68 Stenholm et al., 2013
Quantitative Exploring country-level institutional arrangements on the rate and type of entrepreneurial activity
63 countries' secondary data from the World Bank Group Entrepreneurship Entry Density data, Doing Business Report, Index of Economic Freedom, Global Competitive index and GEM Entrepreneurial Aspirations Data for 2009.
Differences in institutional arrangements are associated with a variance in the rate and type of entrepreneurial activity across countries. To support innovative and high growth/impact entrepreneurial ventures a fourth pillar is required (conducive institutions resulting from knowledge spill-overs and capital necessary for high impact entrepreneurial activity).
330
# Authors Approach Focus of Study Analysed Sample Findings
69 Vanevenhoven and Liguori, 2013
Quantitative cross-sectional
The impact of entrepreneurship education (EE) on the motivation process toward entrepreneurship based on social cognitive career theory. Introducing the EE project data initiative
Phase 1 data from 18,000 students in 70 countries and 141 universities in North America (8327), South America (1645), Eastern Europe (1391), Western Europe (5,213), Africa (723), Middle East (161), Asia-Pacific (1021)
Among other antecedents of EI and competences, number of courses offered in EE significantly correlated with EI across all regions r=0.14 (small effect size). However, number of extra-curricular activities was not significantly related to EI.
70 Veciana et al., 2005
Quantitative cross-sectional
Assessing the role of desirability, feasibility and social norms on entrepreneurial intentions (EI) in different contexts
837 Spanish and 435 Puerto Rican first up to final year university students
Despite high perceived desirability, low perceived feasibility due to barriers on start-up reduces EI.
71 Verheul et al., 2012
Quantitative Moderating and mediating effect of gender on risk taking propensity, locus of control and self-employment preference and activity as well as perception of barriers, support factors in the environment
2004 Data from 29 countries including USA in the Eurobarometer survey by the Enterprise and Industry Department of the European Commission was used. The total number of observations used in this study was 8545 of which 4694 were men and 3851 were women.
Women’s lower preference and actual involvement in self-employment is explained by gender interactions with risk taking propensity, internal locus of control, role models, perception of barriers such as lack of access to finance, unfavourable economic environment and administrative complexities.
331
# Authors Approach Focus of Study Analysed Sample Findings
72 Volery et al., 2013
Quantitative longitudinal 2012-2013
An evaluation of the impact of entrepreneurship education (EE) and personality factors on human capital and entrepreneurial intention (EI).
494 EE upper secondary school students in Switzerland and a control group of 238 students at t1 and 345 and 133 students at t2, respectively.
Need for achievement and risk taking propensity positively significantly impact EI. EE has significant positive but limited impact on human capital assets (knowledge, opportunity identification, evaluation and exploitation). However, human capital assets had no significant impact on EI. In fact, there was a negative impact between knowledge and EI.
73 Von Graevenitz et al., 2010
Quantitative longitudinal 2008-2009
The impact of entrepreneurship education (EE) on entrepreneurial intentions (EI), skills and motivation
Ex-ante and ex-post survey on 357 undergraduate students in 3 months compulsory entrepreneurship module for Business Administration degree- Munich School of Management tLudwig-Maximilian-Unversitat (LMU), Germany.
EI reduced for the class (ex-ante survey 71.4%, ex-post 63.8%). Authors concluded that reduction was because the course helped students sort themselves into whether they are suitable for entrepreneurship or organisational employment based on aptitude self-evaluation. Overall EE led to significant positive effect on students' skills and confidence.
74 Walter et al., 2011
Quantitative cross-sectional
Effect of entrepreneurship education (EE), university level support programmes, industry ties and research orientation on business students' intentions
1530 business students and 132 professors at 25 universities in Germany
EE and industry ties positively related to intentions only for males in the sample. Negative effect of research orientation
75 Wilson et al., 2007
Quantitative cross-sectional
The relationships between gender, entrepreneurial self-efficacy (ESE), and entrepreneurial intentions
For two sample groups: 4292 adolescents in high school and 933 adult MBA students in the USA
The effects of entrepreneurship education in MBA programmes on ESE proved stronger for women than for men.
332
# Authors Approach Focus of Study Analysed Sample Findings
76 Woodier-Harris, 2010
Qualitative cross-sectional
Evaluating the impact of SPEED on students' career choices
15 students interviewed using critical incident technique (CIT) from one of the 13 participating universities 3 months after completing the SPEED programme
Experiential learning approach, mentoring, funding were valuable learning experiences. Results indicate that 73% of students went on to start their businesses while 23% decided starting business was not for them but they admitted they had acquired valuable skills.
77 Wu and Wu, 2008
Quantitative cross-sectional
Effects of diversity of educational background and level on entrepreneurial intention (EI)
150 diploma, undergraduate and postgraduate, engineering and non-engineering, entrepreneurship education (EE) and non-EE students from one university in China
Respondents at diploma and undergraduate level had higher EI than those at postgraduate level. No significant difference in perceived behavioural control (PBC) between EE majors (though they had higher intentions than the rest) and non-EE majors. In fact engineering students had higher PBC and attitude. Attitude was the major predictor of EI.
78 Zellweger et al., 2011
Quantitative cross-sectional
Career intentions of students with family business background
5363 students with family business background from 87 universities in 8 European countries
Females prefer employment to founding. Positive exposure to family business leads to preferring succession intention to founding or employment. Students with higher locus of control are more likely to choose employment. Students with high entrepreneurial self-efficacy are more likely to become successors than employees. Students with higher entrepreneurial self-efficacy are more likely to become founders than successors. Transitively, the higher the motive for independence the higher the intention to found, followed by being a successor and lastly being an employee. The higher the innovation motive the higher the preference for founding than succession. Thus, perceived feasibility does not always lead to desirability (unless the independence and innovative motives are high).
333
# Authors Approach Focus of Study Analysed Sample Findings
79 Zhang et al., 2013
Quantitative cross-sectional
Using Ajzen’s theory of planned behaviour and Shapero’s entrepreneurial event model as well as entrepreneurial cognition theory, the authors attempt to identify the relationship between entrepreneurship education (EE), prior entrepreneurial exposure, perceived desirability and feasibility, and entrepreneurial intentions (EI) for university students.
The data were collected from a survey of ten universities; they received 494 effective responses in Netherlands.
The authors used probit estimation to show that perceived desirability significantly impacts EI whereas there is no significant impact from perceived feasibility. There is a significant negative impact from exposure (which is surprising) and a significant positive impact from EE. Males and people from technological universities and/or backgrounds have higher EI than females and people from other universities and backgrounds. There are also significant positive interaction effects by gender, university type, and study major on the relationship between EE and EI.
80 Zhao et al., 2005
Quantitative longitudinal 1998-2000
The mediating role of self-efficacy in the development of students' entrepreneurial intentions (EI).
Structural equation modelling with a sample of 778 (T1) and 267 (T2) (overall matched sample 265) MBA students across 5 universities in USA
Effects of perceived learning from entrepreneurship related courses, previous entrepreneurial experience and risk taking propensity were fully mediated by entrepreneurial self-efficacy. Gender was not mediated but had a direct effect such that women had lower EI.
81 Zhao et al., 2010
Meta-analyses quantitative
Influence of personality traits using the big five factor model of personality plus risk taking propensity on entrepreneurial intentions (EI) and performance
60 studies with 66 independent samples with total sample size of 15423 individuals
The traits with positive influence on EI in order of effect size were risk taking propensity, openness to experience, emotional stability, conscientiousness, and extraversion. Agreeableness had a negative relationship. Risk taking propensity and agreeableness did not contribute to performance.